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Institute for Pure & Applied Mathematics (IPAM) · Science

Institute for Pure & Applied Mathematics (IPAM)

The Institute for Pure and Applied Mathematics (IPAM) is a National Science Foundation Math Institute at the University of California, Los Angeles (UCLA) that fosters the interaction of mathematics with a broad range of science and technology, builds new interdisciplinary research communities, promotes mathematical innovation, and engages and transforms the world through mathematics. IPAM fulfills its mission through workshops and programs that connect mathematics and other disciplines or multiple areas of mathematics. These activities bring in thousands of visitors annually from academia, government, and industry. The NSF has encouraged IPAM to make the scientific presentations of our speakers available to a wider audience. While this YouTube channel contains many of our most popular videos, our full video archive is available at www.ipam.ucla.edu/videos.

Episodes

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Marcin Lis - Embeddings & Statistical Mechanics (Part 1) - IPAM at UCLA

14 Mar 2024
1h 17m
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Tomas Berggren - Dimer models and random tilings (Part 2) - IPAM at UCLA

14 Mar 2024
1h 13m
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Greta Panova - Symmetric Functions (Part 2) - IPAM at UCLA

14 Mar 2024
1h 15m
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Terrence George - Introduction to cluster algebras (Part 2) - IPAM at UCLA

13 Mar 2024
1h 11m
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Eveliina Peltola - Gaussian free field and Schramm--Loewner Evolution (Part 2) - IPAM at UCLA

13 Mar 2024
1h 18m
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Pavel Galashin - Introduction to cluster algebras (Part 1) - IPAM at UCLA

13 Mar 2024
1h 5m
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Greta Panova - Symmetric Functions (Part 1) - IPAM at UCLA

13 Mar 2024
1h 18m
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Cédric Boutillier - Dimer models and random tilings (Part 1) - IPAM at UCLA

12 Mar 2024
1h 13m
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Nathanael Berestycki - Gaussian free field and Schramm--Loewner Evolution (Part 1) - IPAM at UCLA

12 Mar 2024
1h 18m
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Raghu Meka - Complexity of Sparse Linear Regression - IPAM at UCLA

01 Mar 2024
53m
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Surbhi Goel - Beyond Worst-case Guarantees for Sequential Prediction: Robustness via Abstention

01 Mar 2024
46m
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Pravesh Kothari - Algorithms Approaching the Threshold for Semirandom Planted Clique - IPAM at UCLA

01 Mar 2024
55m
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Arya Mazumdar - Sample complexity of estimation in logistic regression - IPAM at UCLA

01 Mar 2024
56m
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Vatsal Sharan - Memory as a lens to understand efficient learning and optimization - IPAM at UCLA

29 Feb 2024
47m
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Sitan Chen - Provably learning a multi-head attention layer - IPAM at UCLA

29 Feb 2024
49m
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Jelena Diakonikolas - Robust Learning of a Neuron: Bridging Computational Gaps Using Optimization

29 Feb 2024
50m
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Giang Tran - Fast Multipole Attention: A Divide-and-Conquer Attention Mechanism for Long Sequences

29 Feb 2024
41m
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Wasim Huleihel - Testing Dependency of Databases - IPAM at UCLA

29 Feb 2024
45m
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Matus Telgarsky - A Perceptron Trio - IPAM at UCLA

28 Feb 2024
50m
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Cynthia Rush - Is It Easier to Count Communities Than Find Them? - IPAM at UCLA

28 Feb 2024
47m
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