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Dan Roy - Size of Teachers as Measure of Data Complexity: PAC-Bayes Excess Risk Bounds & Scaling Law
Presenter
- Dan Roy
October 16, 2024
IPAM
Shaowei Lin - Singular Learning, Relative Information and the Dual Numbers - IPAM at UCLA
Presenter
- Shaowei Lin
October 16, 2024
IPAM
Paul Riechers - geometric representation of far future in deep neural networks trained on next-token
Presenter
- Paul Riechers
October 16, 2024
IPAM
Blake Bordelon - Infinite limits and scaling laws of neural networks - IPAM at UCLA
Presenter
- Blake Bordelon
October 16, 2024
IPAM
Cengiz Pehlevan - 2 stories in mechanistic interpretation of natural & artificial neural computation
Presenter
- Cengiz Pehlevan
October 15, 2024
IPAM
Vidya Muthukumar - Comparison and transfer between tasks in overparameterized learning
Presenter
- Vidya Muthukumar
October 15, 2024
IPAM
Wu Lin - A framework for designing (non-diagonal) adaptive training methods - IPAM at UCLA
Presenter
- Wu Lin
October 14, 2024
IPAM
Maciej Dolega - Global asymptotics of Jack-deformed random Young diagrams via Lukasiewicz paths
Presenter
- Maciej Dolega
April 19, 2024
IPAM
Jessica Striker - Rotation-invariant web bases, hourglass plabic graphs, symmetrized 6-vertex config
Presenter
- Jessica Striker
April 18, 2024
IPAM
Jehanne Dousse - The Andrews-Gordon partition identities and commutative algebra - IPAM at UCLA
Presenter
- Jehanne Dousse
April 18, 2024
IPAM
Joshua Swanson - Unifying lattices through hourglass plabic graphs - IPAM at UCLA
Presenter
- Joshua Swanson
April 18, 2024
IPAM
Colin Defant - Toric Promotion with Reflections and Refractions - IPAM at UCLA
Presenter
- Colin Defant
April 18, 2024
IPAM