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Workshop
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Revisiting the noise Model of SGD
Barak Battash · Ofir Lindenbaum
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Workshop
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The Noise Geometry of Stochastic Gradient Descent: A Quantitative and Analytical Characterization
Mingze Wang · Lei Wu
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Workshop
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Noise-adaptive (Accelerated) Stochastic Heavy-Ball Momentum
Anh Dang · Reza Babanezhad Harikandeh · Sharan Vaswani
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Poster
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Thu 8:45
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Stability and Generalization of the Decentralized Stochastic Gradient Descent Ascent Algorithm
Miaoxi Zhu · Li Shen · Bo Du · Dacheng Tao
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Poster
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Thu 8:45
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Stochastic Collapse: How Gradient Noise Attracts SGD Dynamics Towards Simpler Subnetworks
Feng Chen · Daniel Kunin · Atsushi Yamamura · Surya Ganguli
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Poster
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Wed 8:45
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Implicit Bias of (Stochastic) Gradient Descent for Rank-1 Linear Neural Network
Bochen Lyu · Zhanxing Zhu
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Poster
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Wed 15:00
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Variance-Reduced Gradient Estimation via Noise-Reuse in Online Evolution Strategies
Oscar Li · James Harrison · Jascha Sohl-Dickstein · Virginia Smith · Luke Metz
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Workshop
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Benign Oscillation of Stochastic Gradient Descent with Large Learning Rate
Miao Lu · Beining Wu · Xiaodong Yang · Difan Zou
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Poster
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Tue 15:15
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Convergence of mean-field Langevin dynamics: time-space discretization, stochastic gradient, and variance reduction
Taiji Suzuki · Denny Wu · Atsushi Nitanda
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Workshop
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Sat 9:25
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Enhancing Low-Precision Sampling via Stochastic Gradient Hamiltonian Monte Carlo
Ziyi Wang · Yujie Chen · Ruqi Zhang · Qifan Song
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Workshop
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A Predicting Clipping Asynchronous Stochastic Gradient Descent Method in Distributed Learning
Haoxiang Wang · Zhanhong Jiang · Chao Liu · Soumik Sarkar · Dongxiang Jiang · Young Lee
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Poster
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Tue 15:15
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Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Stochastic Gradient Descent
Lingjiong Zhu · Mert Gurbuzbalaban · Anant Raj · Umut Simsekli
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