場所：東京都のイベント

Mufan Li (Princeton) 氏による講演 [Deep Learning Theory Team Seminar]

イベント説明

Speaker: Mufan Li (Princeton)
Title: The Proportional Scaling Limit of Neural Networks
Abstract: Recent advances in deep learning performance have all relied on scaling up the number of parameters within neural networks, consequently making asymptotic scaling limits a compelling approach to theoretical analysis. In this talk, we explore the proportional infinite-depth-and-width limit, where the role of depth can be adequately studied, and the limit remains a great model of finite size networks. At initialization, we characterize the limiting distribution of the network via a stochastic differential equation (SDE) for the feature covariance matrix. Furthermore, in the linear network setting, we can also characterize the spectrum of the covariance matrix in the large data limit via a geometric variant of Dyson Brownian motions. Finally, we will briefly discuss ongoing work towards analyzing training dynamics.
(ハイブリッド開催用のzoom URLは講演開始直前に連絡します)

開催日

2025年5月20日14:00 ～ 2025年5月20日15:00

主催者・問い合わせ先

RIKEN AIP Public

開催場所

項目内容
場所522号室
住所〒113-8654 東京都文京区本郷7丁目3-1東京大学工学部14号館522号室

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B!

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