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DTSTART;TZID=America/New_York:20260424T140000
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SUMMARY:Compression Is All You Need: Modeling Mathematics
DESCRIPTION:Freedman Seminar \nSpeaker: Mike Freedman\, Harvard CMSA \nTitle: Compression Is All You Need: Modeling Mathematics \nAbstract: The talk will exposit a recent eponymous arXiv posting with coauthors Vitaly Aksenov\, Eve Bodnia\, and Mike Mulligan. The approach is to think like a physicist and model a seemingly complex bit of reality: mathematics\, by a simple toy model where exact computations can be carried out and then compared with observation.  The models are finitely generated monoids and the data is derived from MathLib a large Lean-based repository. The hierarchical nature of definitions and lemmas in math is modeled by adding redundant generators to the monoids – think of the powers of 10 within the natural numbers which support place notation. Place notation confers an exponential compression of how we describe numbers; exploration of MathLib shows that this theme persists to (human) mathematics writ large. We hope that the observables we describe will help our agents navigate to interesting mathematical destinations. \n 
URL:https://cmsa.fas.harvard.edu/event/freedman_42426/
LOCATION:Virtual
CATEGORIES:Freedman Seminar
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/CMSA-Freedman-Seminar-4.24.26.docx.png
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DTSTART;TZID=America/New_York:20260908T090000
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SUMMARY:The Geometry of Machine Learning 2026
DESCRIPTION:The Geometry of Machine Learning 2026 \nDates: September 8–11\, 2026 \nLocation: Harvard CMSA\, Room G10\, 20 Garden Street\, Cambridge MA 02138 \nOrganizers: Michael R. Douglas (CMSA) and Mike Freedman (CMSA) \n  \nDetails TBA \n  \nSupport provided by Logical Intelligence. \n \n  \n 
URL:https://cmsa.fas.harvard.edu/event/gml_2026/
LOCATION:CMSA 20 Garden Street Cambridge\, Massachusetts 02138 United States
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