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X-WR-CALNAME:Claremont Center for the Mathematical Sciences
X-ORIGINAL-URL:https://colleges.claremont.edu/ccms
X-WR-CALDESC:Events for Claremont Center for the Mathematical Sciences
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DTSTART;TZID=America/Los_Angeles:20251201T161500
DTEND;TZID=America/Los_Angeles:20251201T171500
DTSTAMP:20260405T141724
CREATED:20251126T233248Z
LAST-MODIFIED:20251126T233248Z
UID:3935-1764605700-1764609300@colleges.claremont.edu
SUMMARY:Structure-Aware Adaptive Nonconvex Optimization for Deep Learning and Scientific Computing (Minxin Zhang\, UCLA)
DESCRIPTION:Abstract: Modern machine learning and scientific computing pose optimization challenges of unprecedented scale and complexity\, demanding fundamental advances in both theory and algorithmic design for nonconvex optimization. This talk presents recent advances that address these challenges by exploiting matrix and tensor structures\, integrating adaptivity\, and leveraging sampling techniques. In the first part\, I introduce AdaGO\, a new optimizer that combines orthogonalized momentum updates with adaptive learning rates. Building on the recent success of the Muon optimizer in large language model training\, AdaGO incorporates an AdaGrad-type stepsize that scales orthogonalized update directions by accumulated past gradient norms. This design preserves the structural advantage of orthogonalized updates while adapting stepsizes to noise and the optimization landscape. We establish optimal convergence rates for smooth nonconvex functions and demonstrate improved performance over Muon and Adam on classification and regression tasks. The second part focuses on zeroth-order global optimization. We develop a theoretical framework for inexact proximal point (IPP) methods for global optimization\, establishing convergence guarantees when proximal operators are estimated either deterministically or stochastically. The quadratic regularization in the proximal operator induces a concentrated Gibbs measure landscape that facilitates effective sampling. We propose two sampling-based algorithms: TT-IPP\, which constructs a low-rank tensor-train (TT) approximation using a randomized TT-cross algorithm\, and MC-IPP\, which employs Monte Carlo integration. Both IPP algorithms adaptively balance efficiency and accuracy in proximal operator estimation\, achieving strong performance across diverse benchmark functions and applications. Together\, these works advance structure-aware adaptive first-order optimization for deep learning and zeroth-order global optimization in scientific computing.
URL:https://colleges.claremont.edu/ccms/event/structure-aware-adaptive-nonconvex-optimization-for-deep-learning-and-scientific-computing-minxin-zhang-ucla/
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:20251202T121500
DTEND;TZID=America/Los_Angeles:20251202T131000
DTSTAMP:20260405T141724
CREATED:20250808T202734Z
LAST-MODIFIED:20251120T202437Z
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SUMMARY:Positivity aspects of complete homogeneous symmetric polynomials (Stephan Garcia\, Pomona)
DESCRIPTION:Hunter’s theorem ensures that the complete homogeneous symmetric (CHS) polynomials of even degree are positive definite functions.  We provide new proofs of Hunter’s theorem\, applications to operator theory\, and a noncommutative (NC) generalization that sheds light even on the commutative case.  Surprisingly\, this work emerged from a problem in analytic combinatorics.
URL:https://colleges.claremont.edu/ccms/event/antc-talk-stephan-garcia-pomona-2/
LOCATION:Estella 2099
CATEGORIES:Algebra / Number Theory / Combinatorics Seminar
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251202T160000
DTEND;TZID=America/Los_Angeles:20251202T170000
DTSTAMP:20260405T141724
CREATED:20250917T202344Z
LAST-MODIFIED:20251112T013717Z
UID:3845-1764691200-1764694800@colleges.claremont.edu
SUMMARY:Claremont Topology Seminar: Indraneel Tambe (UCLA)
DESCRIPTION:We welcome all undergraduate/graduate students and faculty to attend topology seminar! \nSpeaker: Indraneel Tambe (UCLA) \nTitle: Steinberg skein relations at roots of unity \nAbstract: This talk discusses some of the relationships between skein theory and the representation theory of quantum sl2 when q is a root of unity. Specifically\, I focus on the Frobenius pullback functor on Uq sl2 representations and see how this relates to Bonahon-Wong’s Frobenius skein homomorphism between Kauffman bracket skein modules. I’ll describe results from my joint work with Vijay Higgins in which we proved what we called Steinberg skein identities and used these in a new proof of the well-definition of the Frobenius skein homomorphism.
URL:https://colleges.claremont.edu/ccms/event/claremont-topology-seminar-ko-honda-ucla/
LOCATION:Fletcher 104\, Pitzer College\, 1050 N Mills Ave\, Claremont\, 91711\, United States
CATEGORIES:Topology Seminar
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251205T110000
DTEND;TZID=America/Los_Angeles:20251205T121500
DTSTAMP:20260405T141724
CREATED:20250923T142446Z
LAST-MODIFIED:20251205T155429Z
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SUMMARY:CCMS Colloquium: Konstantin Zuev (Caltech)
DESCRIPTION:CCMS Colloquium invites you to a talk by Konstantin Zuev (Caltech)\n\n \nTitle: Course-Prerequisite Networks\n \nAbstract: An academic curriculum is a complex system of courses and their interactions that lies at the heart of an academic institution and underlies its educational mission. Understanding these systems is essential for providing high-quality education. Course-prerequisite networks (CPNs) are directed acyclic graphs that model academic curricula by representing courses as nodes and prerequisite relationships between them as directed links. In this talk\, we will show how CPNs can be used to visualize\, analyze\, and optimize curricula; identify key courses; allocate teaching resources; quantify the strength of knowledge flow between departments; and uncover the most influential and interdisciplinary areas of study. The proposed methodology applies to any CPN and is illustrated using a network of courses taught at the California Institute of Technology. If time permits\, we will also discuss three new global CPN measures\, breadth\, depth\, and flux\, which enable macro-scale comparisons of different curricula. We illustrate these measures numerically using three real and synthetic CPNs from the Cyprus University of Technology\, the California Institute of Technology\, and Johns Hopkins University.\n \nBio: Dr. Konstantin Zuev is a Teaching Professor of Computing and Mathematical Sciences at the California Institute of Technology\, where he teaches a variety of courses in mathematics and statistics and conducts research on network science with undergraduate students. He is the author of about 30 papers and a forthcoming book\, Fundamentals of Statistical Inference: Foundations of Data Analysis. His teaching and research have been recognized with several awards: the ASCIT Teaching Award (2018 & 2023)\, the Carver Mead Seed Fund Grant (2023)\, the Graduate Student Council Teaching Award (2023)\, the Humboldt Research Fellowship for Experienced Researchers (2021)\, and the Northrop Grumman Prize for Excellence in Teaching (2019). For more information about his background\, please visit http://www.its.caltech.edu/~zuev/index.html
URL:https://colleges.claremont.edu/ccms/event/ccms-colloquium-konstantin-zuev-caltech/
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
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251206T100000
DTEND;TZID=America/Los_Angeles:20251206T115500
DTSTAMP:20260405T141724
CREATED:20251105T044832Z
LAST-MODIFIED:20251106T214405Z
UID:3919-1765015200-1765022100@colleges.claremont.edu
SUMMARY:GEMS December 6th Session
DESCRIPTION:This GEMS session will be facilitated by Professor Ryan Aschoff from the Claremont Graduate University.\n\n\nTitle: Randomness: Creating Order from Chaos\n\nAbstract: \nFrom the hiss of white noise to the gentle hum of ocean waves\, randomness surrounds us — yet hidden within that chaos lies remarkable order. In this talk\, we’ll explore how unpredictable events\, when viewed collectively\, give rise to smooth and universal patterns. We’ll listen to and visualize the “colors” of noise — white\, pink\, and brown — to see how sound encodes randomness across different frequencies. We’ll discover how unrelated random events\, like coin flips or marble drops\, merge into beautifully predictable bell-shaped distributions. And we’ll watch how diffusion and blurring transform disorder into structure\, revealing the same mathematics behind sound\, heat\, and motion.\n\nAlong the way\, we’ll take part in hands-on activities: generating and analyzing noise spectra\, building simple low-pass “smoothing” filters\, and experimenting with diffusion and random walks to watch chaos become order before our eyes. No advanced math required — just curiosity and a willingness to play with randomness!
URL:https://colleges.claremont.edu/ccms/event/gems-december-6th-session/
LOCATION:Shanahan B450\, Harvey Mudd College\, 301 Platt Blvd.\, Claremont\, 91711\, United States
CATEGORIES:GEMS
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