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DTSTART;TZID=America/New_York:20171002T091500
DTEND;TZID=America/New_York:20171002T173000
DTSTAMP:20260521T205230
CREATED:20230717T172938Z
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SUMMARY:The 2017 Charles River Lectures
DESCRIPTION:Charles River with Bench at Sunset\nJointly organized by Harvard University\, Massachusetts Institute of Technology\, and Microsoft Research New England\, the Charles River Lectures on Probability and Related Topics is a one-day event for the benefit of the greater Boston area mathematics community. \nThe 2017 lectures will take place 9:15am – 5:30pm on Monday\, October 2 at Harvard University  in the Harvard Science Center. \n\n\n\n*************************************************** \nUPDATED LOCATION\nHarvard University\nHarvard Science Center (Halls C & E)\n1 Oxford Street\, Cambridge\, MA 02138 (Map)\nMonday\, October 2\, 2017\n9:15 AM – 5:30 PM\n************************************************** \nPlease note that registration has closed. \nSpeakers:\n\nPaul Bourgade (Courant Institute\, NYU)\nMassimiliano Gubinelli (University of Bonn)\nAndrea Montanari (Stanford University)\nRoman Vershynin (University of California\, Irvine)\nOfer Zeitouni (Weizmann Institute)\n\nAgenda:\nIn Harvard Science Center Hall C: \n8:45 am – 9:15 am: Coffee/light breakfast \n9:15 am – 10:15 am: Ofer Zeitouni \nTitle: Noise stability of the spectrum of large matrices \nAbstract: The spectrum of large non-normal matrices is notoriously sensitive to perturbations\, as the example of nilpotent matrices shows. Remarkably\, the spectrum of these matrices perturbed by polynomially (in the dimension) vanishing additive noise is remarkably stable. I will describe some results and the beginning of a theory. \nThe talk is based on joint work with Anirban Basak and Elliot Paquette\, and earlier works with Feldheim\, Guionnet\, Paquette and Wood.\n\n10:20 am – 11:20 am: Andrea Montanari \nTitle: Algorithms for estimating low-rank matrices  \nAbstract: Many interesting problems in statistics can be formulated as follows. The signal of interest is a large low-rank matrix with additional structure\, and we are given a single noisy view of this matrix. We would like to estimate the low rank signal by taking into account optimally the signal structure. I will discuss two types of efficient estimation procedures based on message-passing algorithms and semidefinite programming relaxations\, with an emphasis on asymptotically exact results. \n11:20 am – 11:45 am: Break \n11:45 am – 12:45 pm: Paul Bourgade \nTitle: Random matrices\, the Riemann zeta function and trees \nAbstract: Fyodorov\, Hiary & Keating have conjectured that the maximum of the characteristic polynomial of random unitary matrices behaves like extremes of log-correlated Gaussian fields. This allowed them to predict the typical size of local maxima of the Riemann zeta function along the critical axis. I will first explain the origins of this conjecture\, and then outline the proof for the leading order of the maximum\, for unitary matrices and the zeta function. This talk is based on joint works with Arguin\, Belius\, Radziwill and Soundararajan. \n1:00 pm – 2:30 pm: Lunch \nIn Harvard Science Center Hall E: \n2:45 pm – 3:45 pm: Roman Vershynin \nTitle: Deviations of random matrices and applications \nAbstract: Uniform laws of large numbers provide theoretical foundations for statistical learning theory. This lecture will focus on quantitative uniform laws of large numbers for random matrices. A range of illustrations will be given in high dimensional geometry and data science. \n3:45 pm – 4:15 pm: Break \n4:15 pm – 5:15 pm: Massimiliano Gubinelli \nTitle: Weak universality and Singular SPDEs \nAbstract: Mesoscopic fluctuations of microscopic (discrete or continuous) dynamics can be described in terms of nonlinear stochastic partial differential equations which are universal: they depend on very few details of the microscopic model. This universality comes at a price: due to the extreme irregular nature of the random field sample paths\, these equations turn out to not be well-posed in any classical analytic sense. I will review recent progress in the mathematical understanding of such singular equations and of their (weak) universality and their relation with the Wilsonian renormalisation group framework of theoretical physics. \nOrganizers:\n Alexei Borodin\, Henry Cohn\, Vadim Gorin\, Elchanan Mossel\, Philippe Rigollet\, Scott Sheffield\, and H.T. Yau
URL:https://cmsa.fas.harvard.edu/event/the-2017-charles-river-lectures/
LOCATION:Harvard Science Center\, 1 Oxford Street\, Cambridge\, MA\, 02138
CATEGORIES:Event,Public Lecture,Special Lectures
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DTSTART;TZID=America/New_York:20171002T090000
DTEND;TZID=America/New_York:20171006T160000
DTSTAMP:20260521T205230
CREATED:20230717T173144Z
LAST-MODIFIED:20250304T211134Z
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SUMMARY:Workshop on Additive Combinatorics\, Oct. 2-6\, 2017
DESCRIPTION:The workshop on additive combinatorics will take place October 2-6\, 2017 at the Center of Mathematical Sciences and Applications\, located at 20 Garden Street\, Cambridge\, MA. \nAdditive combinatorics is a mathematical area bordering on number theory\, discrete mathematics\, harmonic analysis and ergodic theory. It has achieved a number of successes in pure mathematics in the last two decades in quite diverse directions\, such as: \n\nThe first sensible bounds for Szemerédi’s theorem on progressions (Gowers);\nLinear patterns in the primes (Green\, Tao\, Ziegler);\nConstruction of expanding sets in groups and expander graphs (Bourgain\, Gamburd);\nThe Kakeya Problem in Euclidean harmonic analysis (Bourgain\, Katz\, Tao).\n\nIdeas and techniques from additive combinatorics have also had an impact in theoretical computer science\, for example \n\nConstructions of pseudorandom objects (eg. extractors and expanders);\nConstructions of extremal objects (eg. BCH codes);\nProperty testing (eg. testing linearity);\nAlgebraic algorithms (eg. matrix multiplication).\n\nThe main focus of this workshop will be to bring together researchers involved in additive combinatorics\, with a particular inclination towards the links with theoretical computer science. Thus it is expected that a major focus will be additive combinatorics on the boolean cube (Z/2Z)^n \, which is the object where the exchange of ideas between pure additive combinatorics and theoretical computer science is most fruitful. Another major focus will be the study of pseudorandom phenomena in additive combinatorics\, which has been an important contributor to modern methods of generating provably good randomness through deterministic methods. Other likely topics of discussion include the status of major open problems (the polynomial Freiman-Ruzsa conjecture\, inverse theorems for the Gowers norms with bounds\, explicit correlation bounds against low degree polynomials) as well as the impact of new methods such as the introduction of algebraic techniques by Croot–Pach–Lev and Ellenberg–Gijswijt. \nConfirmed participants include: \n\nArnab Bhattacharyya (Indian Institute of Science)\nThomas Bloom (University of Bristol)\nJop Briët (Centrum Wiskunde & Informatica\, Amsterdam)\nMei-Chu Chang (University of California\, Riverside)\nNoam Elkies (Harvard University)\nAsaf Ferber (MIT)\nJacob Fox (Stanford University)\nShafi Goldwasser (MIT)\nElena Grigorescu (Purdue University)\nHamed Hatami (McGill University)\nPooya Hatami (Institute for Advanced Study)\nKaave Hosseini (University of California\, San Diego)\nGuy Kindler (Hebrew University of Jerusalem)\nVsevolod Lev (University of Haifa at Oranim)\nSean Prendiville (University of Manchester)\nRonitt Rubinfeld (MIT)\nWill Sawin (ETH Zürich)\nFernando Shao (Oxford University)\nOlof Sisask (KTH Royal Institute of Technology)\nMadhur Tulsiani (University of Chicago)\nJulia Wolf (University of Bristol)\nEmanuele Viola (Northeastern University)\nYufei Zhao (MIT)\n\nCo-organizers of this workshop include Ben Green\, Swastik Kopparty\, Ryan O’Donnell\, Tamar Ziegler. \nMonday\, October 2 \n\n\n\nTime\nSpeaker\nTitle/Abstract\n\n\n9:00-9:30am\nBreakfast\n \n\n\n9:30-10:20am\nJacob Fox\nTower-type bounds for Roth’s theorem with popular differences \nAbstract: A famous theorem of Roth states that for any $\alpha > 0$ and $n$ sufficiently large in terms of $\alpha$\, any subset of $\{1\, \dots\, n\}$ with density $\alpha$ contains a 3-term arithmetic progression. Green developed an arithmetic regularity lemma and used it to prove that not only is there one arithmetic progression\, but in fact there is some integer $d > 0$ for which the density of 3-term arithmetic progressions with common difference $d$ is at least roughly what is expected in a random set with density $\alpha$. That is\, for every $\epsilon > 0$\, there is some $n(\epsilon)$ such that for all $n > n(\epsilon)$ and any subset $A$ of $\{1\, \dots\, n\}$ with density $\alpha$\, there is some integer $d > 0$ for which the number of 3-term arithmetic progressions in $A$ with common difference $d$ is at least $(\alpha^3-\epsilon)n$. We prove that $n(\epsilon)$ grows as an exponential tower of 2’s of height on the order of $\log(1/\epsilon)$. We show that the same is true in any abelian group of odd order $n$. These results are the first applications of regularity lemmas for which the tower-type bounds are shown to be necessary. \nThe first part of the talk by Jacob Fox includes an overview and discusses the upper bound. The second part of the talk by Yufei Zhao focuses on the lower bound construction and proof. These results are all joint work with Huy Tuan Pham.\n\n\n10:20-11:00am\nCoffee Break\n \n\n\n11:00-11:50am\nYufei Zhao\nTower-type bounds for Roth’s theorem with popular differences \nAbstract:  Continuation of first talk by Jacob Fox. The first part of the talk by Jacob Fox includes an overview and discusses the upper bound. The second part of the talk by Yufei Zhao focuses on the lower bound construction and proof. These results are all joint work with Huy Tuan Pham.\n\n\n12:00-1:30pm\nLunch\n \n\n\n1:30-2:20pm\nJop Briët\nLocally decodable codes and arithmetic progressions in random settings \nAbstract: This talk is about a common feature of special types of error correcting codes\, so-called locally decodable codes (LDCs)\, and two problems on arithmetic progressions in random settings\, random differences in Szemerédi’s theorem and upper tails for arithmetic progressions in a random set in particular. It turns out that all three can be studied in terms of the Gaussian width of a set of vectors given by a collection of certain polynomials. Using a matrix version of the Khintchine inequality and a lemma that turns such polynomials into matrices\, we give an alternative proof for the best-known lower bounds on LDCs and improved versions of prior results due to Frantzikinakis et al. and Bhattacharya et al. on arithmetic progressions in the aforementioned random settings. \nJoint work with Sivakanth Gopi\n\n\n2:20-3:00pm\nCoffee Break\n \n\n\n3:00-3:50pm\nFernando Shao\n\nLarge deviations for arithmetic progressions \nAbstract: We determine the asymptotics of the log-probability that the number of k-term arithmetic progressions in a random subset of integers exceeds its expectation by a constant factor. This is the arithmetic analog of subgraph counts in a random graph. I will highlight some open problems in additive combinatorics that we encountered in our work\, namely concerning the “complexity” of the dual functions of AP-counts. \n\n\n\n4:00-6:00pm\nWelcome Reception\n\n\n\n\nTuesday\, October 3 \n\n\n\nTime\nSpeaker\nTitle/Abstract\n\n\n9:00-9:30am\nBreakfast\n\n\n\n9:30-10:20am\nEmanuele Viola\nInterleaved group products \nAuthors: Timothy Gowers and Emanuele Viola \nAbstract: Let G be the special linear group SL(2\,q). We show that if (a1\,a2) and (b1\,b2) are sampled uniformly from large subsets A and B of G^2 then their interleaved product a1 b1 a2 b2 is nearly uniform over G. This extends a result of Gowers (2008) which corresponds to the independent case where A and B are product sets. We obtain a number of other results. For example\, we show that if X is a probability distribution on G^m such that any two coordinates are uniform in G^2\, then a pointwise product of s independent copies of X is nearly uniform in G^m\, where s depends on m only. Similar statements can be made for other groups as well. \nThese results have applications in computer science\, which is the area where they were first sought by Miles and Viola (2013).\n\n\n10:20-11:00am\nCoffee Break\n\n\n\n11:00-11:50am\nVsevolod Lev\nOn Isoperimetric Stability \nAbstract: We show that a non-empty subset of an abelian group with a small edge boundary must be large; in particular\, if $A$ and $S$ are finite\, non-empty subsets of an abelian group such that $S$ is independent\, and the edge boundary of $A$ with respect to $S$ does not exceed $(1-c)|S||A|$ with a real $c\in(0\,1]$\, then $|A|\ge4^{(1-1/d)c|S|}$\, where $d$ is the smallest order of an element of $S$. Here the constant $4$ is best possible. \nAs a corollary\, we derive an upper bound for the size of the largest independent subset of the set of popular differences of a finite subset of an abelian group. For groups of exponent $2$ and $3$\, our bound translates into a sharp estimate for the additive  dimension of the popular difference set. \nWe also prove\, as an auxiliary result\, the following estimate of possible independent interest: if $A\subseteq{\mathbb Z}^n$ is a finite\, non-empty downset\, then\, denoting by $w(z)$ the number of non-zero components of the vector $z\in\mathbb{Z}^n$\, we have   $$ \frac1{|A|} \sum_{a\in A} w(a) \le \frac12\\, \log_2 |A|. $$\n\n\n12:00-1:30pm\nLunch\n\n\n\n1:30-2:20pm\nElena Grigorescu\nNP-Hardness of Reed-Solomon Decoding and the Prouhet-Tarry-Escott Problem \nAbstract: I will discuss the complexity of decoding Reed-Solomon codes\, and some results establishing NP-hardness for asymptotically smaller decoding radii than the maximum likelihood decoding radius. These results follow from the study of a generalization of the classical Subset Sum problem to higher moments\, which may be of independent interest. I will further discuss a connection with the Prouhet-Tarry-Escott problem studied in Number Theory\, which turns out to capture a main barrier in extending our techniques to smaller radii. \nJoint work with Venkata Gandikota and Badih Ghazi.\n\n\n2:20-3:00pm\nCoffee Break\n\n\n\n3:00-3:50pm\nSean Prendiville\nPartition regularity of certain non-linear Diophantine equations. \nAbstract:  We survey some results in additive Ramsey theory which remain valid when variables are restricted to sparse sets of arithmetic interest\, in particular the partition regularity of a class of non-linear Diophantine equations in many variables.\n\n\n\nWednesday\, October 4 \n\n\n\nTime\nSpeaker\nTitle/Abstract\n\n\n9:00-9:30am\nBreakfast\n \n\n\n9:30-10:20am\nOlof Sisask\nBounds on capsets via properties of spectra \nAbstract: A capset in F_3^n is a subset A containing no three distinct elements x\, y\, z satisfying x+z=2y. Determining how large capsets can be has been a longstanding problem in additive combinatorics\, particularly motivated by the corresponding question for subsets of {1\,2\,…\,N}. While the problem in the former setting has seen spectacular progress recently through the polynomial method of Croot–Lev–Pach and Ellenberg–Gijswijt\, such progress has not been forthcoming in the setting of the integers. Motivated by an attempt to make progress in this setting\, we shall revisit the approach to bounding the sizes of capsets using Fourier analysis\, and in particular the properties of large spectra. This will be a two part talk\, in which many of the ideas will be outlined in the first talk\, modulo the proof of a structural result for sets with large additive energy. This structural result will be discussed in the second talk\, by Thomas Bloom\, together with ideas on how one might hope to achieve Behrend-style bounds using this method. \nJoint work with Thomas Bloom.\n\n\n10:20-11:00am\nCoffee Break\n \n\n\n11:00-11:50am\nThomas Bloom\nBounds on capsets via properties of spectra \nThis is a continuation of the previous talk by Olof Sisask.\n\n\n12:00-1:30pm\nLunch\n \n\n\n1:30-2:20pm\nHamed Hatami\nPolynomial method and graph bootstrap percolation \nAbstract: We introduce a simple method for proving lower bounds for the size of the smallest percolating set in a certain graph bootstrap process. We apply this method to determine the sizes of the smallest percolating sets in multidimensional tori and multidimensional grids (in particular hypercubes). The former answers a question of Morrison and Noel\, and the latter provides an alternative and simpler proof for one of their main results. This is based on a joint work with Lianna Hambardzumyan and Yingjie Qian.\n\n\n2:20-3:00pm\nCoffee Break\n\n\n\n3:00-3:50pm\nArnab Bhattacharyya\nAlgorithmic Polynomial Decomposition \nAbstract: Fix a prime p. Given a positive integer k\, a vector of positive integers D = (D_1\, …\, D_k) and a function G: F_p^k → F_p\, we say a function P: F_p^n → F_p admits a (k\, D\, G)-decomposition if there exist polynomials P_1\, …\, P_k: F_p^n -> F_p with each deg(P_i) <= D_i such that for all x in F_p^n\, P(x) = G(P_1(x)\, …\, P_k(x)). For instance\, an n-variate polynomial of total degree d factors nontrivially exactly when it has a (2\, (d-1\, d-1)\, prod)-decomposition where prod(a\,b) = ab. \nWhen show that for any fixed k\, D\, G\, and fixed bound d\, we can decide whether a given polynomial P(x_1\, …\, x_n) of degree d admits a (k\,D\,G)-decomposition and if so\, find a witnessing decomposition\, in poly(n) time. Our approach is based on higher-order Fourier analysis. We will also discuss improved analyses and algorithms for special classes of decompositions. \nJoint work with Pooya Hatami\, Chetan Gupta and Madhur Tulsiani.\n\n\n\nThursday\, October 5 \n\n\n\nTime\nSpeaker\nTitle/Abstract\n\n\n9:00-9:30am\nBreakfast\n\n\n\n9:30-10:20am\nMadhur Tulsiani\nHigher-order Fourier analysis and approximate decoding of Reed-Muller codes \n Abstract: Decomposition theorems proved by Gowers and Wolf provide an appropriate notion of “Fourier transform” for higher-order Fourier analysis. I will discuss some questions and techniques that arise from trying to develop polynomial time algorithms for computing these decompositions. \nI will discuss constructive proofs of these decompositions based on boosting\, which reduce the problem of computing these decompositions to a certain kind of approximate decoding problem for codes. I will also discuss some earlier and recent works on this decoding problem. \nBased on joint works with Arnab Bhattacharyya\, Eli Ben-Sasson\, Pooya Hatami\, Noga Ron-Zewi and Julia Wolf.\n\n\n10:20-11:00am\nCoffee Break\n\n\n\n11:00-11:50am\nJulia Wolf\nStable arithmetic regularity \nThe arithmetic regularity lemma in the finite-field model\, proved by Green in 2005\, states that given a subset A of a finite-dimensional vector space over a prime field\, there exists a subspace H of bounded codimension such that A is Fourier-uniform with respect to almost all cosets of H. It is known that in general\, the growth of the codimension of H is required to be of tower type depending on the degree of uniformity\, and that one must allow for a small number of non-uniform cosets. \nOur main result is that\, under a natural model-theoretic assumption of stability\, the tower-type bound and non-uniform cosets in the arithmetic regularity lemma are not necessary.  Specifically\, we prove an arithmetic regularity lemma for k-stable subsets in which the bound on the codimension of the subspace is a polynomial (depending on k) in the degree of uniformity\, and in which there are no non-uniform cosets. \nThis is joint work with Caroline Terry. \n\n\n\n12:00-1:30pm\nLunch\n \n\n\n1:30-2:20pm\nWill Sawin\n\nConstructions of Additive Matchings \nAbstract: I will explain my work\, with Robert Kleinberg and David Speyer\, constructing large tri-colored sum-free sets in vector spaces over finite fields\, and how it shows that some additive combinatorics problems over finite fields are harder than corresponding problems over the integers.  \n\n\n\n2:20-3:00pm\nCoffee Break\n\n\n\n3:00-3:50pm\nMei-Chu Chang\nArithmetic progressions in multiplicative groups of finite fields \nAbstract:   Let G be a multiplicative subgroup of the prime field F_p of size |G|> p^{1-\kappa} and r an arbitrarily fixed positive integer. Assuming \kappa=\kappa(r)>0 and p large enough\, it is shown that any proportional subset A of G contains non-trivial arithmetic progressions of length r.\n\n\n\nFriday\, October 6 \n\n\n\nTime\nSpeaker\nTitle/Abstract\n\n\n9:00-9:30am\nBreakfast\n\n\n\n9:30-10:20am\nAsaf Ferber\nOn a resilience version of the Littlewood-Offord problem \nAbstract:  In this talk we consider a resilience version of the classical Littlewood-Offord problem. That is\, consider the sum X=a_1x_1+…a_nx_n\, where the a_i-s are non-zero reals and x_i-s are i.i.d. random variables with     (x_1=1)= P(x_1=-1)=1/2. Motivated by some problems from random matrices\, we consider the question: how many of the x_i-s  can we typically allow an adversary to change without making X=0? We solve this problem up to a constant factor and present a few interesting open problems. \nJoint with: Afonso Bandeira (NYU) and Matthew Kwan (ETH\, Zurich).\n\n\n10:20-11:00am\nCoffee Break\n\n\n\n11:00-11:50am\nKaave Hosseini\nProtocols for XOR functions and Entropy decrement \nAbstract: Let f:F_2^n –> {0\,1} be a function and suppose the matrix M defined by M(x\,y) = f(x+y) is partitioned into k monochromatic rectangles.  We show that F_2^n can be partitioned into affine subspaces of co-dimension polylog(k) such that f is constant on each subspace. In other words\, up to polynomial factors\, deterministic communication complexity and parity decision tree complexity are equivalent. \nThis relies on a novel technique of entropy decrement combined with Sanders’ Bogolyubov-Ruzsa lemma. \nJoint work with Hamed Hatami and Shachar Lovett\n\n\n12:00-1:30pm\nLunch\n\n\n\n1:30-2:20pm\nGuy Kindler\n\nFrom the Grassmann graph to Two-to-Two games \nAbstract: In this work we show a relation between the structure of the so called Grassmann graph over Z_2 and the Two-to-Two conjecture in computational complexity. Specifically\, we present a structural conjecture concerning the Grassmann graph (together with an observation by Barak et. al.\, one can view this as a conjecture about the structure of non-expanding sets in that graph) which turns out to imply the Two-to-Two conjecture. \nThe latter conjecture its the lesser-known and weaker sibling of the Unique-Games conjecture [Khot02]\, which states that unique games (a.k.a. one-to-one games) are hard to approximate. Indeed\, if the Grassmann-Graph conjecture its true\, it would also rule out some attempts to refute the Unique-Games conjecture\, as these attempts provide potentially efficient algorithms to solve unique games\, that would actually also solve two-to-two games if they work at all. \nThese new connections between the structural properties of the Grassmann graph and complexity theoretic conjectures highlight the Grassmann graph as an interesting and worthy object of study. We may indicate some initial results towards analyzing its structure. \nThis is joint work with Irit Dinur\, Subhash Khot\, Dror Minzer\, and Muli Safra. \n\n\n\n\n\n\n\nEvents\,Past Events
URL:https://cmsa.fas.harvard.edu/event/workshop-on-additive-combinatorics-oct-2-6-2017/
LOCATION:CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:Event,Workshop
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170927T134200
DTEND;TZID=America/New_York:20170927T134200
DTSTAMP:20260521T205230
CREATED:20240213T100517Z
LAST-MODIFIED:20240213T100517Z
UID:10002388-1506519720-1506519720@cmsa.fas.harvard.edu
SUMMARY:9-27-17 Mathematical Physics Seminar
DESCRIPTION:
URL:https://cmsa.fas.harvard.edu/event/9-27-17-mathematical-physics-seminar/
LOCATION:MA
CATEGORIES:Mathematical Physics Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170927T134100
DTEND;TZID=America/New_York:20170927T134100
DTSTAMP:20260521T205230
CREATED:20240213T100715Z
LAST-MODIFIED:20240213T100715Z
UID:10002393-1506519660-1506519660@cmsa.fas.harvard.edu
SUMMARY:9-27-17 RM&PT Seminar
DESCRIPTION:
URL:https://cmsa.fas.harvard.edu/event/9-27-17-rmpt-seminar/
LOCATION:MA
CATEGORIES:Random Matrix & Probability Theory Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170918T133900
DTEND;TZID=America/New_York:20170918T133900
DTSTAMP:20260521T205230
CREATED:20240213T100938Z
LAST-MODIFIED:20240213T100938Z
UID:10002396-1505741940-1505741940@cmsa.fas.harvard.edu
SUMMARY:9-18-17 Mathematical Physics Seminar
DESCRIPTION:
URL:https://cmsa.fas.harvard.edu/event/9-18-17-mathematical-physics-seminar/
LOCATION:MA
CATEGORIES:Mathematical Physics Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170914T150000
DTEND;TZID=America/New_York:20170914T160000
DTSTAMP:20260521T205230
CREATED:20240212T072955Z
LAST-MODIFIED:20240212T072955Z
UID:10001875-1505401200-1505404800@cmsa.fas.harvard.edu
SUMMARY:Algebraic Geometry Seminar\, Thursdays
DESCRIPTION:This seminar will not be held in the Spring 2018 Semester. \nThe Algebraic Geometry Seminar will be every Thursday from 3pm-4pm in CMSA Building\, 20 Garden Street\, Room G10. \nThe schedule will be updated as details are confirmed. \n  \n  \n\n\n\nDate\nName\nTitle/Abstract\n\n\n09-14-17\n Yu-Wei Fan (Harvard Math)\n\nEntropy of an autoequivalence on Calami-Yau manifolds \nAbstract:  We will recall the notion of entropy of an autoequivalence on triangulated categories\, and provide counterexamples of a conjecture by Kikuta-Takahashi. \n\n\n\n11-1-17 \n*5:00pm\, G10*\n Shamil Shakirov\, Harvard Math\n\nUndulation invariants of plane curves \nAbstract: “One of the general problems in algebraic geometry is to determine algorithmically whether or not a given geometric object\, defined by explicit polynomial equations (e.g. a curve or a surface)\, satisfies a given property (e.g. has singularities or other distinctive features of interest). A classical example of such a problem\, described by Cayley and Salmon in 1852\, is to determine whether or not a given plane curve of degree r > 3 has undulation points — the points where the tangent line meets the curve with multiplicity four. Cayley proved that there exists an invariant of degree (r – 3)(3 r – 2) that vanishes if and only if the curve has undulation points. We construct this invariant explicitly for quartics (r=4) as the determinant of a 21 times 21 matrix with polynomial entries\, and we conjecture a generalization for r = 5 \n\n\n\n11-2-17 \n \nAlexander Moll\, IHES\n\nHilbert Schemes from Geometric Quantization of Dispersive Periodic Benjamin-Ono Waves \nABSTRACT: By Grojnowski and Nakajima\, Fock spaces are cohomology rings of Hilbert scheme of points in the plane.  On the other hand\, by Pressley-Segal\, Fock spaces are spaces of J-holomorphic functions on the loop space of the real line that appear in geometric quantization with respect to the Kähler structure determined by the Sobolev regularity s= -1/2 and the Hilbert transform J.  First\, we show that the classical periodic Benjamin-Ono equation is a Liouville integrable Hamiltonian system with respect to this Kähler structure.  Second\, we construct an integrable geometric quantization of this system in Fock space following Nazarov-Sklyanin and describe the spectrum explicitly after a non-trivial rewriting of our coefficients of dispersion \ebar = e_1 + e_2 and quantization \hbar = – e_1 e_2 that is invariant under e_2 <-> e_1.  As a corollary of Lehn’s theorem\, our construction gives explicit creation and annihilation operator formulas for multiplication by new explicit universal polynomials in the Chern classes of the tautological bundle in the equivariant cohomology of our Hilbert schemes\, in particular identifying \ebar with the deformation parameter of the Maulik-Okounkov Yangian and \hbar with the handle-gluing element.  Our key ingredient is a simple formula for the Lax operators as elliptic generalized Toeplitz operators on the circle together with the spectral theory of Boutet de Monvel and Guillemin.  As time permits\, we discuss the relation of dispersionless \ebar -> 0 and semi-classical \hbar \rightarrow 0 limits to Nekrasov’s BPS/CFT Correspondence. \n\n\n\n11-9-17\n  TBD\n  TBD\n\n\n11-16-17\n TBD\n TBD\n\n\n11-23-17\n  TBD\n  TBD\n\n\n11-30-17\n  TBD\n  TBD\n\n\n12-7-17\n  TBD\n  TBD\n\n\n12-15-17\n  TBD\n  TBD
URL:https://cmsa.fas.harvard.edu/event/algebraic-geometry-seminar-thursdays/
LOCATION:MA
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170911T133800
DTEND;TZID=America/New_York:20170911T133800
DTSTAMP:20260521T205230
CREATED:20240213T101213Z
LAST-MODIFIED:20240213T101213Z
UID:10002400-1505137080-1505137080@cmsa.fas.harvard.edu
SUMMARY:9/11/2017 Mathematical Physics Seminar
DESCRIPTION:
URL:https://cmsa.fas.harvard.edu/event/9-11-2017-mathematical-physics-seminar/
LOCATION:MA
CATEGORIES:Mathematical Physics Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170908T130000
DTEND;TZID=America/New_York:20170908T160000
DTSTAMP:20260521T205230
CREATED:20240209T112503Z
LAST-MODIFIED:20240209T112503Z
UID:10001855-1504875600-1504886400@cmsa.fas.harvard.edu
SUMMARY:Combinatorics & Complexity Seminar\, Fridays
DESCRIPTION:The seminar on Combinatorics and Complexity will be held every Friday from 1:00-4:00pm in CMSA Building\, 20 Garden Street\, Room G10. \nThe list of speakers for the upcoming academic year will be posted below and updated as details are confirmed. Titles and abstracts for the talks will be added as they are received. \nAdditional information on CMSA’s Combinatorics and Complexity program can be found here. \n  \n\n\n\nDate\nName\nTitle/Abstract\n\n\n09-08-17\n\nTBA\n\n\n09-15-2017\n\nTBA\n\n\n09-22-17\n\nTBA\n\n\n09-29-17\n\nTBA\n\n\n10-06-17\n\n TBA\n\n\n10-13-2017\n\nTBA\n\n\n10-20-2017\n\nTBA\n\n\n10-27-2017\n\nTBA\n\n\n11-03-2017\n\nTBA\n\n\n11-10-2017\n\nTBA\n\n\n11-17-2017\n\nTBA\n\n\n11-24-2017\n\nTBA\n\n\n12-01-2017\n\nTBA\n\n\n12-08-2017\n\n TBA
URL:https://cmsa.fas.harvard.edu/event/combinatorics-complexity-seminar-fridays/
LOCATION:MA
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170907T170000
DTEND;TZID=America/New_York:20170907T180000
DTSTAMP:20260521T205230
CREATED:20230717T172748Z
LAST-MODIFIED:20250305T183135Z
UID:10000035-1504803600-1504807200@cmsa.fas.harvard.edu
SUMMARY:Noga Alon Public Talk
DESCRIPTION:Noga Alon (Tel Aviv University) will be giving a public talk on September 7\, 2017\,as part of the program on combinatorics and complexity hosted by the CMSA during AY17-18.  The talk will be at 5:00pm in Askwith Hall\, 13 Appian Way\, Cambridge\, MA. \nTitle: Graph Coloring: Local and Global \nAbstract: Graph Coloring is arguably the most popular subject in Discrete Mathematics\, and its combinatorial\, algorithmic and computational aspects have been studied intensively. The most basic notion in the area\, the chromatic number of a graph\, is an inherently global property. This is demonstrated by the hardness of computation or approximation of this invariant as well as by the existence of graphs with arbitrarily high chromatic number and no short cycles. The investigation of these graphs had a profound impact on Graph Theory and Combinatorics. It combines combinatorial\, probabilistic\, algebraic and topological techniques with number theoretic tools. I will describe the rich history of the subject focusing on some recent results. \n 
URL:https://cmsa.fas.harvard.edu/event/noga-alon-public-talk-9-7-17/
LOCATION:MA
CATEGORIES:Event,Public Lecture
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/Noga-Poster-2-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170818T154700
DTEND;TZID=America/New_York:20170819T154700
DTSTAMP:20260521T205230
CREATED:20230717T172600Z
LAST-MODIFIED:20250328T144515Z
UID:10000034-1503071220-1503157620@cmsa.fas.harvard.edu
SUMMARY:2017 Big Data Conference
DESCRIPTION:The Center of Mathematical Sciences and Applications will be hosting a conference on Big Data from August 18 – 19\, 2017\, in Hall D of the Science Center at Harvard University.\nThe Big Data Conference features many speakers from the Harvard community as well as scholars from across the globe\, with talks focusing on computer science\, statistics\, math and physics\, and economics. This is the third conference on Big Data the Center will host as part of our annual events\, and is co-organized by Richard Freeman\, Scott Kominers\, Jun Liu\, Horng-Tzer Yau and Shing-Tung Yau. \nConfirmed Speakers: \n\nMohammad Akbarpour\, Stanford University\nAlbert-László Barabási\, Northeastern University\nNoureddine El Karoui\, University of California\, Berkeley\nRavi Jagadeesan\, Harvard University\nLucas Janson\, Harvard University\nTracy Ke\, University of Chicago\nTze Leung Lai\, Stanford University\nAnnie Liang\, University of Pennsylvania\nMarena Lin\, Harvard University\nNikhil Naik\, Harvard University\nAlex Peysakhovich\, Facebook\nNatesh Pillai\, Harvard University\nJann Spiess\, Harvard University\nBradly Stadie\, Open AI\, University of California\, Berkeley\nZak Stone\, Google\nHau-Tieng Wu\, University of Toronto\nSifan Zhou\, Xiamen University\n\n  \nFollowing the conference\, there will be a two-day workshop from August 20-21. The workshop is organized by Scott Kominers\, and will feature: \n\nJörn Boehnke\, Harvard University\nNikhil Naik\, Harvard University\nBradly Stadie\, Open AI\, University of California\, Berkeley\n\n  \nConference Schedule \nA PDF version of the schedule below can also be downloaded here. \nAugust 18\, Friday (Full day)\n\n\n\nTime\nSpeaker\nTopic\n\n\n8:30 am – 9:00 am\n\nBreakfast\n\n\n9:00 am – 9:40 am\nMohammad Akbarpour \nVideo\nTitle: Information aggregation in overlapping generations and the emergence of experts \nAbstract: We study a model of social learning with “overlapping generations”\, where agents meet others and share data about an underlying state over time. We examine under what conditions the society will produce individuals with precise knowledge about the state of the world. There are two information sharing regimes in our model: Under the full information sharing technology\, individuals exchange the information about their point estimates of an underlying state\, as well as their sources (or the precision of their signals) and update their beliefs by taking a weighted average. Under the limited information sharing technology\, agents only observe the information about the point estimates of those they meet\, and update their beliefs by taking a weighted average\, where weights can depend on the sequence of meetings\, as well as the labels. Our main result shows that\, unlike most social learning settings\, using such linear learning rules do not guide the society (or even a fraction of its members) to learn the truth\, and having access to\, and exploiting knowledge of the precision of a source signal are essential for efficient social learning (joint with Amin Saberi & Ali Shameli).\n\n\n9:40 am – 10:20 am\nLucas Janson \nVideo\nTitle: Model-Free Knockoffs For High-Dimensional Controlled Variable Selection \nAbstract: Many contemporary large-scale applications involve building interpretable models linking a large set of potential covariates to a response in a nonlinear fashion\, such as when the response is binary. Although this modeling problem has been extensively studied\, it remains unclear how to effectively control the fraction of false discoveries even in high-dimensional logistic regression\, not to mention general high-dimensional nonlinear models. To address such a practical problem\, we propose a new framework of model-free knockoffs\, which reads from a different perspective the knockoff procedure (Barber and Candès\, 2015) originally designed for controlling the false discovery rate in linear models. The key innovation of our method is to construct knockoff variables probabilistically instead of geometrically. This enables model-free knockoffs to deal with arbitrary (and unknown) conditional models and any dimensions\, including when the dimensionality p exceeds the sample size n\, while the original knockoffs procedure is constrained to homoscedastic linear models with n greater than or equal to p. Our approach requires the design matrix be random (independent and identically distributed rows) with a covariate distribution that is known\, although we show our procedure to be robust to unknown/estimated distributions. As we require no knowledge/assumptions about the conditional distribution of the response\, we effectively shift the burden of knowledge from the response to the covariates\, in contrast to the canonical model-based approach which assumes a parametric model for the response but very little about the covariates. To our knowledge\, no other procedure solves the controlled variable selection problem in such generality\, but in the restricted settings where competitors exist\, we demonstrate the superior power of knockoffs through simulations. Finally\, we apply our procedure to data from a case-control study of Crohn’s disease in the United Kingdom\, making twice as many discoveries as the original analysis of the same data. \nSlides\n\n\n10:20 am – 10:50 am\n\nBreak\n\n\n10:50 pm – 11:30 pm\nNoureddine El Karoui \nVideo\nTitle: Random matrices and high-dimensional statistics: beyond covariance matrices \nAbstract: Random matrices have played a central role in understanding very important statistical methods linked to covariance matrices (such as Principal Components Analysis\, Canonical Correlation Analysis etc…) for several decades. In this talk\, I’ll show that one can adopt a random-matrix-inspired point of view to understand the performance of other widely used tools in statistics\, such as M-estimators\, and very common methods such as the bootstrap. I will focus on the high-dimensional case\, which captures well the situation of “moderately” difficult statistical problems\, arguably one of the most relevant in practice. In this setting\, I will show that random matrix ideas help upend conventional theoretical thinking (for instance about maximum likelihood methods) and highlight very serious practical problems with resampling methods.\n\n\n11:30 am – 12:10 pm\nNikhil Naik \nVideo\nTitle: Understanding Urban Change with Computer Vision and Street-level Imagery \nAbstract: Which neighborhoods experience physical improvements? In this work\, we introduce a computer vision method to measure changes in the physical appearances of neighborhoods from time-series street-level imagery. We connect changes in the physical appearance of five US cities with economic and demographic data and find three factors that predict neighborhood improvement. First\, neighborhoods that are densely populated by college-educated adults are more likely to experience physical improvements. Second\, neighborhoods with better initial appearances experience\, on average\, larger positive improvements. Third\, neighborhood improvement correlates positively with physical proximity to the central business district and to other physically attractive neighborhoods. Together\, our results illustrate the value of using computer vision methods and street-level imagery to understand the physical dynamics of cities. \n(Joint work with Edward L. Glaeser\, Cesar A. Hidalgo\, Scott Duke Kominers\, and Ramesh Raskar.)\n\n\n12:10 pm – 12:25 pm\nVideo #1 \nVideo #2\nData Science Lightning Talks\n\n\n12:25 pm – 1:30 pm\n\nLunch\n\n\n1:30 pm – 2:10 pm\nTracy Ke \nVideo\nTitle: A new SVD approach to optimal topic estimation \nAbstract: In the probabilistic topic models\, the quantity of interest—a low-rank matrix consisting of topic vectors—is hidden in the text corpus matrix\, masked by noise\, and Singular Value Decomposition (SVD) is a potentially useful tool for learning such a low-rank matrix. However\, the connection between this low-rank matrix and the singular vectors of the text corpus matrix are usually complicated and hard to spell out\, so how to use SVD for learning topic models faces challenges. \nWe overcome the challenge by revealing a surprising insight: there is a low-dimensional simplex structure which can be viewed as a bridge between the low-rank matrix of interest and the SVD of the text corpus matrix\, and which allows us to conveniently reconstruct the former using the latter. Such an insight motivates a new SVD-based approach to learning topic models. \nFor asymptotic analysis\, we show that under a popular topic model (Hofmann\, 1999)\, the convergence rate of the l1-error of our method matches that of the minimax lower bound\, up to a multi-logarithmic term. In showing these results\, we have derived new element-wise bounds on the singular vectors and several large deviation bounds for weakly dependent multinomial data. Our results on the convergence rate and asymptotical minimaxity are new. We have applied our method to two data sets\, Associated Process (AP) and Statistics Literature Abstract (SLA)\, with encouraging results. In particular\, there is a clear simplex structure associated with the SVD of the data matrices\, which largely validates our discovery.\n\n\n2:10 pm – 2:50 pm\nAlbert-László Barabási \nVideo\nTitle: Taming Complexity: From Network Science to Controlling Networks \nAbstract: The ultimate proof of our understanding of biological or technological systems is reflected in our ability to control them. While control theory offers mathematical tools to steer engineered and natural systems towards a desired state\, we lack a framework to control complex self-organized systems. Here we explore the controllability of an arbitrary complex network\, identifying the set of driver nodes whose time-dependent control can guide the system’s entire dynamics. We apply these tools to several real networks\, unveiling how the network topology determines its controllability. Virtually all technological and biological networks must be able to control their internal processes. Given that\, issues related to control deeply shape the topology and the vulnerability of real systems. Consequently unveiling the control principles of real networks\, the goal of our research\, forces us to address series of fundamental questions pertaining to our understanding of complex systems. \n \n\n\n2:50 pm – 3:20 pm\n\nBreak\n\n\n3:20 pm – 4:00 pm\nMarena Lin \nVideo\nTitle: Optimizing climate variables for human impact studies \nAbstract: Estimates of the relationship between climate variability and socio-economic outcomes are often limited by the spatial resolution of the data. As studies aim to generalize the connection between climate and socio-economic outcomes across countries\, the best available socio-economic data is at the national level (e.g. food production quantities\, the incidence of warfare\, averages of crime incidence\, gender birth ratios). While these statistics may be trusted from government censuses\, the appropriate metric for the corresponding climate or weather for a given year in a country is less obvious. For example\, how do we estimate the temperatures in a country relevant to national food production and therefore food security? We demonstrate that high-resolution spatiotemporal satellite data for vegetation can be used to estimate the weather variables that may be most relevant to food security and related socio-economic outcomes. In particular\, satellite proxies for vegetation over the African continent reflect the seasonal movement of the Intertropical Convergence Zone\, a band of intense convection and rainfall. We also show that agricultural sensitivity to climate variability differs significantly between countries. This work is an example of the ways in which in-situ and satellite-based observations are invaluable to both estimates of future climate variability and to continued monitoring of the earth-human system. We discuss the current state of these records and potential challenges to their continuity.\n\n\n4:00 pm – 4:40 pm\nAlex Peysakhovich\n Title: Building a cooperator \nAbstract: A major goal of modern AI is to construct agents that can perform complex tasks. Much of this work deals with single agent decision problems. However\, agents are rarely alone in the world. In this talk I will discuss how to combine ideas from deep reinforcement learning and game theory to construct artificial agents that can communicate\, collaborate and cooperate in productive positive sum interactions.\n\n\n4:40 pm – 5:20 pm\nTze Leung Lai \nVideo\nTitle: Gradient boosting: Its role in big data analytics\, underlying mathematical theory\, and recent refinements \nAbstract: We begin with a review of the history of gradient boosting\, dating back to the LMS algorithm of Widrow and Hoff in 1960 and culminating in Freund and Schapire’s AdaBoost and Friedman’s gradient boosting and stochastic gradient boosting algorithms in the period 1999-2002 that heralded the big data era. The role played by gradient boosting in big data analytics\, particularly with respect to deep learning\, is then discussed. We also present some recent work on the mathematical theory of gradient boosting\, which has led to some refinements that greatly improves the convergence properties and prediction performance of the methodology.\n\n\n\nAugust 19\, Saturday (Full day)\n\n\n\nTime\nSpeaker\nTopic\n\n\n8:30 am – 9:00 am\n\nBreakfast\n\n\n9:00 am – 9:40 am\nNatesh Pillai \nVideo\nTitle: Accelerating MCMC algorithms for Computationally Intensive Models via Local Approximations \nAbstract: We construct a new framework for accelerating Markov chain Monte Carlo in posterior sampling problems where standard methods are limited by the computational cost of the likelihood\, or of numerical models embedded therein. Our approach introduces local approximations of these models into the Metropolis–Hastings kernel\, borrowing ideas from deterministic approximation theory\, optimization\, and experimental design. Previous efforts at integrating approximate models into inference typically sacrifice either the sampler’s exactness or efficiency; our work seeks to address these limitations by exploiting useful convergence characteristics of local approximations. We prove the ergodicity of our approximate Markov chain\, showing that it samples asymptotically from the exact posterior distribution of interest. We describe variations of the algorithm that employ either local polynomial approximations or local Gaussian process regressors. Our theoretical results reinforce the key observation underlying this article: when the likelihood has some local regularity\, the number of model evaluations per Markov chain Monte Carlo (MCMC) step can be greatly reduced without biasing the Monte Carlo average. Numerical experiments demonstrate multiple order-of-magnitude reductions in the number of forward model evaluations used in representative ordinary differential equation (ODE) and partial differential equation (PDE) inference problems\, with both synthetic and real data.\n\n\n9:40 am – 10:20 am\nRavi Jagadeesan \nVideo\nTitle: Designs for estimating the treatment effect in networks with interference \nAbstract: In this paper we introduce new\, easily implementable designs for drawing causal inference from randomized experiments on networks with interference. Inspired by the idea of matching in observational studies\, we introduce the notion of considering a treatment assignment as a quasi-coloring” on a graph. Our idea of a perfect quasi-coloring strives to match every treated unit on a given network with a distinct control unit that has identical number of treated and control neighbors. For a wide range of interference functions encountered in applications\, we show both by theory and simulations that the classical Neymanian estimator for the direct effect has desirable properties for our designs. This further extends to settings where homophily is present in addition to interference.\n\n\n10:20 am – 10:50 am\n\nBreak\n\n\n10:50 am – 11:30 am\nAnnie Liang \nVideo\nTitle: The Theory is Predictive\, but is it Complete? An Application to Human Generation of Randomness \nAbstract: When we test a theory using data\, it is common to focus on correctness: do the predictions of the theory match what we see in the data? But we also care about completeness: how much of the predictable variation in the data is captured by the theory? This question is difficult to answer\, because in general we do not know how much “predictable variation” there is in the problem. In this paper\, we consider approaches motivated by machine learning algorithms as a means of constructing a benchmark for the best attainable level of prediction.  We illustrate our methods on the task of predicting human-generated random sequences. Relative to a theoretical machine learning algorithm benchmark\, we find that existing behavioral models explain roughly 15 percent of the predictable variation in this problem. This fraction is robust across several variations on the problem. We also consider a version of this approach for analyzing field data from domains in which human perception and generation of randomness has been used as a conceptual framework; these include sequential decision-making and repeated zero-sum games. In these domains\, our framework for testing the completeness of theories provides a way of assessing their effectiveness over different contexts; we find that despite some differences\, the existing theories are fairly stable across our field domains in their performance relative to the benchmark. Overall\, our results indicate that (i) there is a significant amount of structure in this problem that existing models have yet to capture and (ii) there are rich domains in which machine learning may provide a viable approach to testing completeness (joint with Jon Kleinberg and Sendhil Mullainathan).\n\n\n11:30 am – 12:10 pm\nZak Stone \nVideo\nTitle: TensorFlow: Machine Learning for Everyone \nAbstract: We’ve witnessed extraordinary breakthroughs in machine learning over the past several years. What kinds of things are possible now that weren’t possible before? How are open-source platforms like TensorFlow and hardware platforms like GPUs and Cloud TPUs accelerating machine learning progress? If these tools are new to you\, how should you get started? In this session\, you’ll hear about all of this and more from Zak Stone\, the Product Manager for TensorFlow on the Google Brain team.\n\n\n12:10 pm – 1:30 pm\n\nLunch\n\n\n1:30 pm – 2:10 pm\nJann Spiess \nVideo\nTitle: (Machine) Learning to Control in Experiments \nAbstract: Machine learning focuses on high-quality prediction rather than on (unbiased) parameter estimation\, limiting its direct use in typical program evaluation applications. Still\, many estimation tasks have implicit prediction components. In this talk\, I discuss accounting for controls in treatment effect estimation as a prediction problem. In a canonical linear regression framework with high-dimensional controls\, I argue that OLS is dominated by a natural shrinkage estimator even for unbiased estimation when treatment is random; suggest a generalization that relaxes some parametric assumptions; and contrast my results with that for another implicit prediction problem\, namely the first stage of an instrumental variables regression.\n\n\n2:10 pm – 2:50 pm\nBradly Stadie\nTitle: Learning to Learn Quickly: One-Shot Imitation and Meta Learning \nAbstract: Many reinforcement learning algorithms are bottlenecked by data collection costs and the brittleness of their solutions when faced with novel scenarios.\nWe will discuss two techniques for overcoming these shortcomings. In one-shot imitation\, we train a module that encodes a single demonstration of a desired behavior into a vector containing the essence of the demo. This vector can subsequently be utilized to recover the demonstrated behavior. In meta-learning\, we optimize a policy under the objective of learning to learn new tasks quickly. We show meta-learning methods can be accelerated with the use of auxiliary objectives. Results are presented on grid worlds\, robotics tasks\, and video game playing tasks.\n\n\n2:50 pm – 3:20 pm\n\nBreak\n\n\n3:20 pm – 4:00 pm\nHau-Tieng Wu \nVideo\nTitle: When Medical Challenges Meet Modern Data Science \nAbstract: Adaptive acquisition of correct features from massive datasets is at the core of modern data analysis. One particular interest in medicine is the extraction of hidden dynamics from a single observed time series composed of multiple oscillatory signals\, which could be viewed as a single-channel blind source separation problem. The mathematical and statistical problems are made challenging by the structure of the signal which consists of non-sinusoidal oscillations with time varying amplitude/frequency\, and by the heteroscedastic nature of the noise. In this talk\, I will discuss recent progress in solving this kind of problem by combining the cepstrum-based nonlinear time-frequency analysis and manifold learning technique. A particular solution will be given along with its theoretical properties. I will also discuss the application of this method to two medical problems – (1) the extraction of a fetal ECG signal from a single lead maternal abdominal ECG signal; (2) the simultaneous extraction of the instantaneous heart/respiratory rate from a PPG signal during exercise; (3) (optional depending on time) an application to atrial fibrillation signals. If time permits\, the clinical trial results will be discussed.\n\n\n4:00 pm – 4:40 pm\nSifan Zhou \nVideo\nTitle: Citing People Like Me: Homophily\, Knowledge Spillovers\, and Continuing a Career in Science \nAbstract: Forward citation is widely used to measure the scientific merits of articles. This research studies millions of journal article citation records in life sciences from MEDLINE and finds that authors of the same gender\, the same ethnicity\, sharing common collaborators\, working in the same institution\, or being geographically close are more likely (and quickly) to cite each other than predicted by their proportion among authors working on the same research topics. This phenomenon reveals how social and geographic distances influence the quantity and speed of knowledge spillovers. Given the importance of forward citations in academic evaluation system\, citation homophily potentially put authors from minority group at a disadvantage. I then show how it influences scientists’ chances to survive in the academia and continue publishing. Based on joint work with Richard Freeman.\n\n\n\n  \nTo view photos and video interviews from the conference\, please visit the CMSA blog. \n\n \n\n  \n\n\n\nBig Data\,CMSA\,Harvard\,Math\nEvents\,Past Events
URL:https://cmsa.fas.harvard.edu/event/2017-big-data-conference-aug-18-19/
LOCATION:Harvard Science Center\, 1 Oxford Street\, Cambridge\, MA\, 02138
CATEGORIES:Big Data Conference,Conference,Event
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/Big-Data-2017_2.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170605T090000
DTEND;TZID=America/New_York:20170606T170000
DTSTAMP:20260521T205230
CREATED:20230717T175551Z
LAST-MODIFIED:20250305T182141Z
UID:10000032-1496653200-1496768400@cmsa.fas.harvard.edu
SUMMARY:A Celebration of Symplectic Geometry: 15 Years of JSG
DESCRIPTION:In celebration of the Journal of Symplectic Geometry’s 15th anniversary\, the Center of Mathematical Sciences and Applications will be hosting A Celebration of Symplectic Geometry: 15 Years of JSG on June 5-6\, 2017. \nConfirmed speakers: \n\nRoger Casals\, MIT\nChen He\, Northeastern University\nYael Karshon\, University of Toronto\nAilsa Keating\, Institute of Advanced Study\nEckhard Meinrenken\, University of Toronto\nAna Rita Pires\, Fordham University\nSobhan Seyfaddini\, Institute of Advanced Study\nAlejandro Uribe\, University of Michigan\nJonathan Weitsman\, Northeastern University\n\nThe conference is co-organized by Denis Auroux and Victor Guillemin. Additional information on the conference will be announced closer to the event. \nSchedule:\nJune 5\, Monday (Full day)\n\n\n\nTime\nSpeaker\nTopic\n\n\n8:30am – 9:0am\n\nBreakfast\n\n\n9:00am – 10:00am\nJonathan Weitsman\nTitle: On the geometric quantization of (some) Poisson manifolds\n\n\n10:30am – 11:30am\nEckhard Meinrenken\nTitle: On Hamiltonian loop group spaces \nAbstract: Let G be a compact Lie group. We explain a construction of an LG-equivariant spinor module over any Hamiltonian loop group space with proper moment map. It may be regarded as its `canonical spin-c structure’. We show how to reduce to finite dimensions\, resulting in actual spin-s structure on transversals\, as well as twisted spin-c structures for the associated quasi-hamiltonian space. This is based on joint work with Yiannis Loizides and Yanli Song.\n\n\n\n11:30am – 1:30pm\n\nBreak\n\n\n1:30pm – 2:30pm\nAna Rita Pires\nTitle: Infinite staircases in symplectic embedding problems \nAbstract: McDuff and Schlenk studied an embedding capacity function\, which describes when a 4-dimensional ellipsoid can symplectically embed into a 4-ball. The graph of this function includes an infinite staircase related to the odd index Fibonacci numbers. Infinite staircases have been shown to exist also in the graphs of the embedding capacity functions when the target manifold is a polydisk or the ellipsoid E(2\,3). I will describe how we use ECH capacities\, lattice point counts and Ehrhart theory to show that infinite staircases exist for these and a few other target manifolds\, as well as to conjecture that these are the only such target manifolds. This is a joint work with Cristofaro-Gardiner\, Holm and Mandini. \nVideo\n\n\n3:00pm – 4:00pm\nSobhan Seyfaddini\nTitle: Rigidity of conjugacy classes in groups of area-preserving homeomorphisms \nAbstract: Motivated by understanding the algebraic structure of groups of area-preserving homeomorphims F. Beguin\, S. Crvoisier\, and F. Le Roux were lead to the following question: Can the conjugacy class of a Hamiltonian homeomorphism be dense? We will show that one can rule out existence of dense conjugacy classes by simply counting fixed points. This is joint work with Le Roux and Viterbo.\n\n\n4:30pm – 5:30pm\nRoger Casals\nTitle: Differential Algebra of Cubic Graphs\nAbstract: In this talk we will associate a combinatorial dg-algebra to a cubic planar graph. This algebra is defined by counting binary sequences\, which we introduce\, and we shall provide explicit computations and examples. From there we study the Legendrian surfaces behind these constructions\, including Legendrian surgeries\, the count of Morse flow trees involved in contact homology\, and the relation to microlocal sheaves. Time permitting\, I will explain a connection to spectral networks.Video\n\n\n\nJune 6\, Tuesday (Full day) \n\n\n\nTime\nSpeaker\nTopic\n\n\n8:30am – 9:00am\n\nBreakfast\n\n\n9:00am – 10:00am\nAlejandro Uribe\nTitle: Semi-classical wave functions associated with isotropic submanifolds of phase space \nAbstract: After reviewing fundamental ideas on the quantum-classical correspondence\, I will describe how to associate spaces of semi-classical wave functions to isotropic submanifolds of phase space satisfying a Bohr-Sommerfeld condition. Such functions have symbols that are symplectic spinors\, and they satisfy a symbol calculus under the action of quantum observables. This is the semi-classical version of the Hermite distributions of Boutet the Monvel and Guillemin\, and it is joint work with Victor Guillemin and Zuoqin Wang. I will inlcude applications and open questions. \nVideo\n\n\n10:30am – 11:30am\nAlisa Keating\nTitle: Symplectomorphisms of exotic discs \nAbstract: It is a theorem of Gromov that the group of compactly supported symplectomorphisms of R^4\, equipped with the standard symplectic form\, is contractible. While nothing is known in higher dimensions for the standard symplectic form\, we show that for some exotic symplectic forms on R^{4n}\, for all but finitely n\, there exist compactly supported symplectomorphisms that are smoothly non-trivial. The principal ingredients are constructions of Milnor and Munkres\, a symplectic and contact version of the Gromoll filtration\, and Borman\, Eliashberg and Murphy’s work on existence of over-twisted contact structures. Joint work with Roger Casals and Ivan Smith. \nVideo\n\n\n11:30am – 1:30pm\n\nBreak\n\n\n1:30pm – 2:30pm\nChen He\nTitle: Morse theory on b-symplectic manifolds \nAbstract: b-symplectic (or log-symplectic) manifolds are Poisson manifolds equipped with symplectic forms of logarithmic singularity. Following Guillemin\, Miranda\, Pires and Scott’s introduction of Hamiltonian group actions on b-symplectic manifolds\, we will survey those classical results of Hamiltonian geometry to the b-symplectic case. \nVideo\n\n\n3:00pm – 4:00pm\nYael Karshon\nTitle: Geometric quantization with metaplectic-c structures \nAbstract: I will present a variant of the Kostant-Souriau geometric quantization procedure that uses metaplectic-c structures to incorporate the “half form correction” into the prequantization stage. This goes back to the late 1970s but it is not widely known and it has the potential to generalize and improve upon recent works on geometric quantization. \nVideo\n\n\n\n 
URL:https://cmsa.fas.harvard.edu/event/a-celebration-of-symplectic-geometry-15-years-of-jsg-june-5-6-2017/
LOCATION:20 Garden Street\, Cambridge\, MA 02138\, MA\, MA\, 02138\, United States
CATEGORIES:Conference,Event
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/Shlomo_orange.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170523T133200
DTEND;TZID=America/New_York:20170523T133200
DTSTAMP:20260521T205230
CREATED:20230801T174602Z
LAST-MODIFIED:20240209T152416Z
UID:10000033-1495546320-1495546320@cmsa.fas.harvard.edu
SUMMARY:5/23/2017 CMSA Special Seminar
DESCRIPTION:
URL:https://cmsa.fas.harvard.edu/event/5-23-2017-cmsa-special-seminar/
LOCATION:CMSA Room G10\, CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:Special Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170503T132900
DTEND;TZID=America/New_York:20170503T132900
DTSTAMP:20260521T205230
CREATED:20240213T102956Z
LAST-MODIFIED:20240213T102956Z
UID:10002432-1493818140-1493818140@cmsa.fas.harvard.edu
SUMMARY:5-3-2017 Random Matrix & Probability Theory Seminar
DESCRIPTION:
URL:https://cmsa.fas.harvard.edu/event/5-3-2017-random-matrix-probability-theory-seminar/
LOCATION:MA
CATEGORIES:Random Matrix & Probability Theory Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170502T133000
DTEND;TZID=America/New_York:20170502T133000
DTSTAMP:20260521T205230
CREATED:20240213T102711Z
LAST-MODIFIED:20240213T102711Z
UID:10002427-1493731800-1493731800@cmsa.fas.harvard.edu
SUMMARY:5-2-2017 Social Sciences Application Forum
DESCRIPTION:
URL:https://cmsa.fas.harvard.edu/event/5-2-2017-social-sciences-application-forum/
LOCATION:MA
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170501T090000
DTEND;TZID=America/New_York:20170502T170000
DTSTAMP:20260521T205230
CREATED:20230717T175324Z
LAST-MODIFIED:20240209T152357Z
UID:10000031-1493629200-1493744400@cmsa.fas.harvard.edu
SUMMARY:Working Conference on Covariance Analysis in Biology\, May 1-4\, 2017
DESCRIPTION:The Center of Mathematical Sciences and Applications will be hosting a working Conference on Covariance Analysis in Biology\, May 1-4\, 2017.  The conference will be hosted in Room G10 of the CMSA Building located at 20 Garden Street\, Cambridge\, MA 02138. \nThis event is open and free.  If you would like to attend\, please register here to help us keep a headcount. A list of lodging options convenient to the Center can also be found on our recommended lodgings page. \nSpeakers: \nOrr Ashenberg\, Fred Hutchinson Cancer Research Center \nJohn Barton\, Massachusetts Institute of Technology \nSimona Cocco\, Laboratoire de Physique Statistique de l’ENS \nSean Eddy\, Harvard University \nEfthimios Kaxiras\, Harvard University \n\n\n\nMichael Laub\, Massachusetts Institute of Technology \nDebora S. Marks\, Harvard University \n\n\n\nGovind Menon\, Brown University \nRémi Monasson\, Laboratoire de Physique Théorique de l’ENS \nAndrew Murray\, Harvard University \nIlya Nemenman\, Emory College \n\n\n\nChris Sander\, Dana-Farber Cancer Institute\, Harvard Medical School \n\n\n\nDave Thirumalai\, University of Texas at Austin \nMartin Weigt\, IBPS\, Université Pierre et Marie Curie \nMatthieu Wyart\, EPFL \nMore speakers will be confirmed soon. \n  \n\n\n\nSchedule:\n(Please click here for a downloadable version of the schedule.)\nPlease note that the schedule for both days is currently tentative and is subject to change.\nMay 1\, Monday \n\n\n\n\n\nTime\nSpeaker\nTopic\n\n\n9:00-10:00am\nSean Eddy\nTBA\n\n\n10:00-11:00am\nMike Laub\nTBA\n\n\n11:00am-12:00pm\nIlya Nemenman\nTBA\n\n\n\n\nMay 2\, Tuesday\n\n\n\n\n\nTime\nSpeaker\nTopic\n\n\n9:00-10:00am\nOrr Ashenberg\nTBA\n\n\n10:00-11:00am\nDebora Marks\nTBA\n\n\n11:00am-12:00pm\nMartin Weigt\nTBA\n\n\n4:30pm-5:30pm\nSimona Cocco\nCMSA Colloquia\n\n\n\n  \n\nMay 3\, Wednesday\n\n\n\n\n\nTime\nSpeaker\nTopic\n\n\n9:00-10:00am\nAndrew Murray\nTBA\n\n\n10:00-11:00am\nMatthieu Wyart\nTBA\n\n\n11:00am-12:00pm\nRémi Monasson\nTBA\n\n\n\n  \n\nMay 4\, Thursday\n\n\n\n\nTime\nSpeaker\nTopic\n\n\n9:00-10:00am\nDavid Thirumalai\nTBA\n\n\n10:00-11:00am\nChris Sander\nTBA\n\n\n11:00am-12:00pm\nJohn Barton\nTBA\n\n\n\n  \n\n\nOrganizers: \n\n\n\nMichael Brenner\, Lucy Colwell\, Elena Rivas\, Eugene Shakhnovich \n\n\n\n* This event is sponsored by CMSA Harvard University. \n\n\n\n\nPast Events
URL:https://cmsa.fas.harvard.edu/event/working-conference-on-covariance-analysis-in-biology-may-1-4-2017/
LOCATION:20 Garden Street\, Cambridge\, MA 02138\, MA\, MA\, 02138\, United States
CATEGORIES:Conference,Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170428T090000
DTEND;TZID=America/New_York:20170502T170000
DTSTAMP:20260521T205230
CREATED:20230717T175015Z
LAST-MODIFIED:20250305T215930Z
UID:10000030-1493370000-1493744400@cmsa.fas.harvard.edu
SUMMARY:JDG 2017 Conference
DESCRIPTION:In celebration of the Journal of Differential Geometry’s 50th anniversary\, the Harvard Math Department will be hosting the Tenth Conference on Geometry and Topology (JDG 2017) from April 28 – May 2\, 2017. \nConfirmed Speakers \n\nMina Aganagic\, UC Berkeley\nDenis Auroux\, UC Berkeley\nCaucher Birkar\, University of Cambridge\nHuai-Dong Cao\, Lehigh University\nTristan Collins\, Harvard University\nCamillo De Lellis\, ETH Zurich\nJean-Pierre Demailly\, Grenoble Alpes University\nSimon Donaldson\, Stony Brook University\nDan Freed\, University of Texas at Austin\nKenji Fukaya\, Stony Brook University\nDavid Gabai\, Princeton University\nLarry Guth\, Massachusetts Institute of Technology\nRichard Hamilton\, Columbia University\nYujiro Kawamata\, University of Tokyo\nFrances Kirwan\, Oxford University\nBlaine Lawson\, Stony Brook University\nJun Li\, Stanford University\nSi Li\, Tsinghua University\nBong Lian\, Brandeis University\nChiu-Chu Melissa Liu\, Columbia University\nCiprian Manolescu\, University of California\, Los Angeles\nFernando Marques\, Princeton University\nWilliam Meeks\, University of Massachusetts Amherst\nWilliam Minicozzi\, Massachusetts Institute of Technology\nJohn Pardon\, Princeton University\nDuong Phong\, Columbia University\nAlena Pirutka\, Courant Institute of New York University\nRichard Schoen\, University of California\, Irvine\nArtan Sheshmani\, QGM Aarhus University/Harvard University\nCliff Taubes\, Harvard University\nCumrun Vafa\, Harvard University\nMu-Tao Wang\, Columbia University\nShing-Tung Yau\, Harvard University\nSteve Zelditch\, Northwestern University\n\n* This event is co-sponsored by Lehigh University and partially supported by the National Science Foundation.
URL:https://cmsa.fas.harvard.edu/event/jdg-2017-conference-april-28-may-2-2017/
LOCATION:Harvard Science Center\, 1 Oxford Street\, Cambridge\, MA\, 02138
CATEGORIES:Conference,Event
ATTACH;FMTTYPE=image/jpeg:https://cmsa.fas.harvard.edu/media/JDG-2017-scaled.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170427T132100
DTEND;TZID=America/New_York:20170427T132100
DTSTAMP:20260521T205230
CREATED:20230801T174502Z
LAST-MODIFIED:20231221T075008Z
UID:10000029-1493299260-1493299260@cmsa.fas.harvard.edu
SUMMARY:4-27-2017 CMSA Special Seminar
DESCRIPTION:
URL:https://cmsa.fas.harvard.edu/event/4-27-2017-cmsa-special-seminar/
LOCATION:MA
CATEGORIES:Special Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170424T133100
DTEND;TZID=America/New_York:20170424T133100
DTSTAMP:20260521T205230
CREATED:20240213T102519Z
LAST-MODIFIED:20240213T102519Z
UID:10002422-1493040660-1493040660@cmsa.fas.harvard.edu
SUMMARY:4-24-2017 Mathematical Physics Seminar
DESCRIPTION:
URL:https://cmsa.fas.harvard.edu/event/4-24-2017-mathematical-physics-seminar/
LOCATION:MA
CATEGORIES:Mathematical Physics Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170423T090000
DTEND;TZID=America/New_York:20170424T170000
DTSTAMP:20260521T205230
CREATED:20230717T174601Z
LAST-MODIFIED:20250304T181313Z
UID:10000028-1492938000-1493053200@cmsa.fas.harvard.edu
SUMMARY:Workshop on Quantum Information
DESCRIPTION:The Center of Mathematical Sciences and Applications will be hosting a workshop on Quantum Information on April 23-24\, 2018. In the days leading up to the conference\, the American Mathematical Society will also be hosting a sectional meeting on quantum information on April 21-22. You can find more information here. \nThe following speakers are confirmed: \n\nFernando G.S.L Brandão (CalTech)\nJacob Biamonte (Skoltech)\nIsaac Chuang (MIT)\nIris Cong (Harvard)\nAram Harrow (MIT)\nKe Li (HIT)\nMikhail D. Lukin (Harvard)\nShunlong Luo (AMSS)\nRenato Renner (ETH Zürich)\nPeter Shor (MIT)
URL:https://cmsa.fas.harvard.edu/event/workshop-on-quantum-information/
LOCATION:20 Garden Street\, Cambridge\, MA 02138\, MA\, MA\, 02138\, United States
CATEGORIES:Event,Workshop
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170419T132200
DTEND;TZID=America/New_York:20170419T132200
DTSTAMP:20260521T205230
CREATED:20240213T092921Z
LAST-MODIFIED:20240213T092921Z
UID:10002336-1492608120-1492608120@cmsa.fas.harvard.edu
SUMMARY:4-19-2017 Random Matrix & Probability Theory Seminar
DESCRIPTION:
URL:https://cmsa.fas.harvard.edu/event/4-19-2017-random-matrix-probability-theory-seminar/
LOCATION:MA
CATEGORIES:Random Matrix & Probability Theory Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170418T110000
DTEND;TZID=America/New_York:20170418T120000
DTSTAMP:20260521T205230
CREATED:20240213T093734Z
LAST-MODIFIED:20240220T144719Z
UID:10002348-1492513200-1492516800@cmsa.fas.harvard.edu
SUMMARY:4-18-2017 Social Science Applications Forum
DESCRIPTION:
URL:https://cmsa.fas.harvard.edu/event/4-18-2017-social-science-applications-forum/
LOCATION:CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170417T131400
DTEND;TZID=America/New_York:20170417T131400
DTSTAMP:20260521T205230
CREATED:20240213T094054Z
LAST-MODIFIED:20240213T094054Z
UID:10002355-1492434840-1492434840@cmsa.fas.harvard.edu
SUMMARY:4-17-2017 Mathematical Physics Seminar
DESCRIPTION:
URL:https://cmsa.fas.harvard.edu/event/4-17-2017-mathematical-physics-seminar/
LOCATION:MA
CATEGORIES:Mathematical Physics Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170414T124600
DTEND;TZID=America/New_York:20170414T124600
DTSTAMP:20260521T205230
CREATED:20240213T100101Z
LAST-MODIFIED:20240213T100101Z
UID:10002378-1492173960-1492173960@cmsa.fas.harvard.edu
SUMMARY:4-14-2017 Special Lecture Series
DESCRIPTION:
URL:https://cmsa.fas.harvard.edu/event/4-14-2017-special-lecture-series/
LOCATION:MA
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170412T125300
DTEND;TZID=America/New_York:20170412T125300
DTSTAMP:20260521T205230
CREATED:20240213T095445Z
LAST-MODIFIED:20240213T095445Z
UID:10002368-1492001580-1492001580@cmsa.fas.harvard.edu
SUMMARY:4-12-2017 Social Science Applications Forum
DESCRIPTION:
URL:https://cmsa.fas.harvard.edu/event/4-12-2017-social-science-applications-forum/
LOCATION:MA
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170412T124400
DTEND;TZID=America/New_York:20170412T124400
DTSTAMP:20260521T205230
CREATED:20240213T100333Z
LAST-MODIFIED:20240213T100333Z
UID:10002385-1492001040-1492001040@cmsa.fas.harvard.edu
SUMMARY:4-12-2017 Special Lecture Series
DESCRIPTION:
URL:https://cmsa.fas.harvard.edu/event/4-12-2017-special-lecture-series/
LOCATION:MA
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170412T115600
DTEND;TZID=America/New_York:20170412T115600
DTSTAMP:20260521T205230
CREATED:20240213T093903Z
LAST-MODIFIED:20240227T113239Z
UID:10002351-1491998160-1491998160@cmsa.fas.harvard.edu
SUMMARY:04-12-2017 Random Matrix & Probability Theory Seminar
DESCRIPTION:
URL:https://cmsa.fas.harvard.edu/event/04-12-2017-random-matrix-probability-theory-seminar/
LOCATION:MA
CATEGORIES:Random Matrix & Probability Theory Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170411T130000
DTEND;TZID=America/New_York:20170411T130000
DTSTAMP:20260521T205230
CREATED:20240213T094754Z
LAST-MODIFIED:20240213T094754Z
UID:10002365-1491915600-1491915600@cmsa.fas.harvard.edu
SUMMARY:4-11-2017 Social Science Applications Forum
DESCRIPTION:
URL:https://cmsa.fas.harvard.edu/event/4-11-2017-social-science-applications-forum/
LOCATION:MA
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170410T130700
DTEND;TZID=America/New_York:20170410T130700
DTSTAMP:20260521T205230
CREATED:20240213T094427Z
LAST-MODIFIED:20240213T094427Z
UID:10002360-1491829620-1491829620@cmsa.fas.harvard.edu
SUMMARY:4-10-2017 Mathematical Physics Seminar
DESCRIPTION:
URL:https://cmsa.fas.harvard.edu/event/4-10-2017-mathematical-physics-seminar/
LOCATION:MA
CATEGORIES:Mathematical Physics Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170407T124300
DTEND;TZID=America/New_York:20170407T124300
DTSTAMP:20260521T205230
CREATED:20240213T100607Z
LAST-MODIFIED:20240213T100607Z
UID:10002391-1491568980-1491568980@cmsa.fas.harvard.edu
SUMMARY:4-7-2017 Special Lecture Series
DESCRIPTION:
URL:https://cmsa.fas.harvard.edu/event/4-7-2017-special-lecture-series/
LOCATION:MA
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170406T125100
DTEND;TZID=America/New_York:20170406T125100
DTSTAMP:20260521T205230
CREATED:20230801T174359Z
LAST-MODIFIED:20231221T074635Z
UID:10000027-1491483060-1491483060@cmsa.fas.harvard.edu
SUMMARY:4-6-2017 CMSA Special Seminar
DESCRIPTION:
URL:https://cmsa.fas.harvard.edu/event/4-6-2017-cmsa-special-seminar/
LOCATION:MA
CATEGORIES:Special Seminar
END:VEVENT
END:VCALENDAR