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Poster
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Mon 17:00
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Proximal Gradient Descent-Ascent: Variable Convergence under KŁ Geometry
Ziyi Chen · Yi Zhou · Tengyu Xu · Yingbin Liang
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Poster
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Wed 17:00
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Local Convergence Analysis of Gradient Descent Ascent with Finite Timescale Separation
Tanner Fiez · Lillian J Ratliff
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Oral
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Thu 0:30
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Optimal Rates for Averaged Stochastic Gradient Descent under Neural Tangent Kernel Regime
Atsushi Nitanda · Taiji Suzuki
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Spotlight
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Wed 5:15
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Benefit of deep learning with non-convex noisy gradient descent: Provable excess risk bound and superiority to kernel methods
Taiji Suzuki · Akiyama Shunta
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Poster
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Wed 1:00
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Byzantine-Resilient Non-Convex Stochastic Gradient Descent
Zeyuan Allen-Zhu · Faeze Ebrahimianghazani · Jerry Li · Dan Alistarh
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Poster
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Thu 9:00
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Linear Last-iterate Convergence in Constrained Saddle-point Optimization
Chen-Yu Wei · Chung-Wei Lee · Mengxiao Zhang · Haipeng Luo
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Poster
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Tue 9:00
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On the Origin of Implicit Regularization in Stochastic Gradient Descent
Samuel Smith · Benoit Dherin · David Barrett · Soham De
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Poster
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Mon 9:00
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Multi-Level Local SGD: Distributed SGD for Heterogeneous Hierarchical Networks
Timothy Castiglia · Anirban Das · Stacy Patterson
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Poster
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Mon 9:00
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On the Impossibility of Global Convergence in Multi-Loss Optimization
Alistair Letcher
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Poster
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Mon 17:00
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When does preconditioning help or hurt generalization?
Shun-ichi Amari · Jimmy Ba · Roger Grosse · Xuechen Li · Atsushi Nitanda · Taiji Suzuki · Denny Wu · Ji Xu
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Spotlight
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Wed 20:20
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Understanding the role of importance weighting for deep learning
Da Xu · Yuting Ye · Chuanwei Ruan
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Poster
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Mon 1:00
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On the Universality of the Double Descent Peak in Ridgeless Regression
David Holzmüller
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