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SUMMARY:Peano: Learning Formal Mathematical Reasoning Without Human Data
DESCRIPTION:New Technologies in Mathematics Seminar \nSpeaker: Gabriel Poesia\, Dept. of Computer Science\, Stanford University \nTitle: Peano: Learning Formal Mathematical Reasoning Without Human Data \nAbstract: Peano is a theorem proving environment in which a computational agent can start tabula rasa in a new domain\, learn to solve problems through curiosity-driven exploration\, and create its own higher level actions. Gabriel will describe the system\, present case studies on learning to solve simple algebra problems from the Khan Academy platform\, and describe work on progress on learning the Natural Number Game\, a popular introduction to theorem proving in Lean for mathematicians. \n 
URL:https://cmsa.fas.harvard.edu/event/nt-11823/
LOCATION:CMSA Room G10\, CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:New Technologies in Mathematics Seminar
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/NTM-11.08.2023.png
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SUMMARY:Fitting ellipsoids to random points
DESCRIPTION:Probability Seminar \nSpeaker: Antoine Maillard (ETH Zürich) \nTitle: Fitting ellipsoids to random points \nAbstract: We consider the problem of exactly fitting an ellipsoid (centered at 0) to n standard Gaussian random vectors in dimension d\, for very large n and d. This problem has connections to questions in statistical learning and theoretical computer science\, and is conjectured to undergo a sharp transition: with high probability\, it has a solution if n < d^2/4\, while it is not satisfiable if n > d^2/4. In this talk we will discuss the origin of this conjecture\, and highlight some recent progress\, in three different directions: \n\nA proof that the problem is feasible for n < d^2 / C\, for some (large) constant C\, significantly improving over previously-known bounds.\nA non-rigorous characterization of the conjecture\, as well as significant generalizations\, using analytical methods of statistical physics.\nA rigorous proof of a satisfiability transition exactly at n = d^2 / 4 in a slightly relaxed version of the problem\, the first rigorous result characterizing the expected phase transition in ellipsoid fitting. The proof is inspired by the non-rigorous characterization discussed above.\n\nThis talk is based on the three manuscripts: arXiv:2307.01181\, arXiv:2310.01169\, arXiv:2310.05787\, which are joint works with A. Bandeira\, Tim Kunisky\, Shahar Mendelson and Elliot Paquette.
URL:https://cmsa.fas.harvard.edu/event/probability-11823/
LOCATION:Virtual
CATEGORIES:Probability Seminar
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