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X-WR-CALDESC:Events for Claremont Center for the Mathematical Sciences
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DTSTART;TZID=America/Los_Angeles:20251027T161500
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UID:3885-1761581700-1761585300@colleges.claremont.edu
SUMMARY:Estimating Shapley Values for Explainable AI via Richer Model Approximations (Teal Witter\, CMC)
DESCRIPTION:Abstract: Modern machine learning is ultimately a simple process: We iteratively update the weights of machine learning models to minimize a problem-specific loss. When it works well\, we deploy the model in human-facing domains like healthcare\, finance\, or the justice system. But even though we know how models are trained\, we don’t understand why they make decisions the decision they do. A particularly compelling approach to explaining AI predictions is the Shapley value\, a game-theoretic quantity that measures how each input to the model affects its output. Mathematically\, the ith Shapley value is the average change in the ith dimension of a particular function defined on the d-dimensional hypercube. Because the hypercube has 2^d points\, exactly computing Shapley values is infeasible. In this talk\, we will instead leverage algorithmic insights to develop state-of-the-art approximation methods.
URL:https://colleges.claremont.edu/ccms/event/estimating-shapley-values-for-explainable-ai-via-richer-model-approximations-teal-witter-cmc/
LOCATION:Emmy Noether Room\, Estella 1021\, Pomona College\,\, 610 N. College Ave.\, Claremont\, CA\, 91711\, United States
CATEGORIES:Applied Math Seminar
ORGANIZER;CN="Ryan Aschoff":MAILTO:ryan.aschoff@cgu.edu
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251028T121500
DTEND;TZID=America/Los_Angeles:20251028T131000
DTSTAMP:20260504T123417
CREATED:20250813T050114Z
LAST-MODIFIED:20251023T042930Z
UID:3784-1761653700-1761657000@colleges.claremont.edu
SUMMARY:From sparsity of rational points on curves to the generic positivity of Beilinson-Bloch height (Ziyang Gao\, UCLA)
DESCRIPTION:It is a fundamental question to find rational solutions to a given system of polynomials\, and in modern language this translates into finding rational points in algebraic varieties.  It is already very deep for algebraic curves defined over Q.  An intrinsic natural number associated with the curve\, called its genus\, plays an important role in studying rational points on curves.  In 1983\, Faltings proved the famous Mordell Conjecture (proposed in 1922)\, which asserts that any curve of genus at least 2 has only finitely many rational points.  Thus the problem for curves of genus at least 2 can be divided into several grades: finiteness\, bound\, uniform bound\, effectiveness.  An answer to each grade requires a better understanding of the distribution of the rational points.\n\nIn my talk\, I will explain the historical and recent developments of this problem according to the different grades.  I will also mention a recent work (joint with Shouwu Zhang) about a generic positivity property and a Northcott property of the Beilison-Bloch height of the Gross-Schoen cycles and the Ceresa cycles.
URL:https://colleges.claremont.edu/ccms/event/antc-talk-ziyang-gao-ucla/
LOCATION:Estella 2099
CATEGORIES:Algebra / Number Theory / Combinatorics Seminar
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DTSTART;TZID=America/Los_Angeles:20251031T110000
DTEND;TZID=America/Los_Angeles:20251031T121500
DTSTAMP:20260504T123417
CREATED:20250923T141345Z
LAST-MODIFIED:20251030T024823Z
UID:3862-1761908400-1761912900@colleges.claremont.edu
SUMMARY:CCMS Colloquium: Anna Ma (UCI)
DESCRIPTION:CCMS Colloquium invites you to a talk by Anna Ma (UCI)\n\n \nTitle: Stochastic iterative methods for solving tensor linear systems\n \nAbstract: Solving linear systems is a crucial subroutine and challenge in data science and scientific computing. Classical approaches for solving linear systems assume that data is readily available and small enough to be stored in memory. However\, in the large-scale data setting\, data may be so large that only partitions (e.g.\, single rows/columns of the matrix/tensor) can be utilized at a time. In this presentation\, we discuss the advantages and role of randomization in iterative methods for approximating the solution to large-scale linear systems. Time permitting\, we will also discuss our recent work on applications to solving systems involving higher-dimensional arrays\, or tensors. Unlike previously proposed randomized iterative strategies\, such as the tensor randomized Kaczmarz method (row slice method) or the tensor Gauss-Seidel method (column slice method)\, which are natural extensions of their matrix counterparts\, our approach delves into a distinct scenario utilizing frontal slice sketching.\n \nBio: Dr. Anna Ma is an Assistant Professor at UC Irvine in the Department of Mathematics. Prior to her position at UCI\, she was a Visiting Assistant Professor at UCI and a UC Chancellor’s Postdoctoral Fellow at UC San Diego in the Department of Mathematics. Her research interests are in randomized algorithms\, numerical linear algebra\, and the mathematics of data science. She is also interested in data visualization and unsupervised machine learning. Anna earned her BS in Mathematics at UC Los Angeles. She received her PhD in Computational Science from Claremont Graduate University and the Computational Science Research Center at San Diego State University\, where she studied the design and analysis of algorithms that solve problems involving large-scale data. \n 
URL:https://colleges.claremont.edu/ccms/event/ccms-colloquium-anna-ma-uci/
LOCATION:Davidson Lecture Hall\, CMC\, 340 E 9th St\, Claremont\, CA\, 91711\, United States
CATEGORIES:Colloquium
ORGANIZER;CN="Bahar Acu":MAILTO:Bahar_Acu@pitzer.edu
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DTSTART;TZID=America/Los_Angeles:20251101T100000
DTEND;TZID=America/Los_Angeles:20251101T115500
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CREATED:20251006T221917Z
LAST-MODIFIED:20251015T083012Z
UID:3886-1761991200-1761998100@colleges.claremont.edu
SUMMARY:GEMS November 1st Session
DESCRIPTION:This GEMS session will be facilitated by Grace Akinwande from the Claremont Graduate University.\n\n\nTitle: From Pizza to Calculus: Understanding Area Through Approximation\n\nAbstract: How much more pizza do you really get from a larger size? In this presentation\, we explore the concept of area starting from an everyday question—the pizza dilemma! We’ll review basic geometric areas and extend the idea to regions bounded by curves. Using simple rectangular approximations\, we’ll discover how increasing the number of rectangles improves accuracy and leads us naturally to the concept of limits. By connecting geometry\, algebra\, and reasoning\, this session illustrates how real-world problems can introduce fundamental ideas of calculus in a fun and intuitive way.
URL:https://colleges.claremont.edu/ccms/event/gems-november-1st-session/
LOCATION:Shanahan B450\, Harvey Mudd College\, 301 Platt Blvd.\, Claremont\, 91711\, United States
CATEGORIES:GEMS
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