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Poster
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Tue 9:00
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Privacy of Noisy Stochastic Gradient Descent: More Iterations without More Privacy Loss
Jason Altschuler · Kunal Talwar
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Poster
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Tue 9:00
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Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Functions
Saeed Masiha · Saber Salehkaleybar · Niao He · Negar Kiyavash · Patrick Thiran
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Poster
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Tue 9:00
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Active Labeling: Streaming Stochastic Gradients
Vivien Cabannes · Francis Bach · Vianney Perchet · Alessandro Rudi
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Poster
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Thu 9:00
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Hidden Progress in Deep Learning: SGD Learns Parities Near the Computational Limit
Boaz Barak · Benjamin Edelman · Surbhi Goel · Sham Kakade · Eran Malach · Cyril Zhang
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Poster
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Thu 9:00
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Implicit Regularization or Implicit Conditioning? Exact Risk Trajectories of SGD in High Dimensions
Courtney Paquette · Elliot Paquette · Ben Adlam · Jeffrey Pennington
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Poster
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Wed 9:00
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Asynchronous SGD Beats Minibatch SGD Under Arbitrary Delays
Konstantin Mishchenko · Francis Bach · Mathieu Even · Blake Woodworth
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Poster
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Wed 9:00
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Risk Bounds of Multi-Pass SGD for Least Squares in the Interpolation Regime
Difan Zou · Jingfeng Wu · Vladimir Braverman · Quanquan Gu · Sham Kakade
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Poster
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Escaping Saddle Points with Bias-Variance Reduced Local Perturbed SGD for Communication Efficient Nonconvex Distributed Learning
Tomoya Murata · Taiji Suzuki
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Poster
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Tue 9:00
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Fine-tuning Language Models over Slow Networks using Activation Quantization with Guarantees
Jue WANG · Binhang Yuan · Luka Rimanic · Yongjun He · Tri Dao · Beidi Chen · Christopher Ré · Ce Zhang
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Poster
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Thu 14:00
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Variance Reduced ProxSkip: Algorithm, Theory and Application to Federated Learning
Grigory Malinovsky · Kai Yi · Peter Richtarik
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Poster
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Thu 14:00
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Sharper Convergence Guarantees for Asynchronous SGD for Distributed and Federated Learning
Anastasiia Koloskova · Sebastian Stich · Martin Jaggi
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Poster
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Thu 9:00
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Accelerating SGD for Highly Ill-Conditioned Huge-Scale Online Matrix Completion
Jialun Zhang · Hong-Ming Chiu · Richard Y Zhang
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