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Michael Crawshaw

Publication record assembled from the DBLP archive of ranked conferences.

Papers indexed

7

Venues

3

Active years

2022–2026

Best venue rank

A*

Where they publish

Papers

7 indexed papers, newest first.

YearVenueTitleAuthors
2026COLTTight Bounds for Logistic Regression with Large Stepsize Gradient Descent in Low Dimension.Michael Crawshaw, Mingrui Liu
2025ICLRComplexity Lower Bounds of Adaptive Gradient Algorithms for Non-convex Stochastic Optimization under Relaxed Smoothness.Michael Crawshaw, Mingrui Liu
2025ICLRLocal Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression.Michael Crawshaw, Blake Woodworth, Mingrui Liu
2025ICMLConstant Stepsize Local GD for Logistic Regression: Acceleration by Instability.Michael Crawshaw, Blake Woodworth, Mingrui Liu
2024ICMLProvable Benefits of Local Steps in Heterogeneous Federated Learning for Neural Networks: A Feature Learning Perspective.Yajie Bao, Michael Crawshaw, Mingrui Liu
2023ICLREPISODE: Episodic Gradient Clipping with Periodic Resampled Corrections for Federated Learning with Heterogeneous Data.Michael Crawshaw, Yajie Bao, Mingrui Liu
2022ICMLFast Composite Optimization and Statistical Recovery in Federated Learning.Yajie Bao, Michael Crawshaw, Shan Luo, Mingrui Liu