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04/26/2022
Beyond Lipschitz: Sharp Generalization and Excess Risk Bounds for Full-Batch GD
We provide sharp path-dependent generalization and excess error guarante...
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03/17/2022
Learning Distributionally Robust Models at Scale via Composite Optimization
To train machine learning models that are robust to distribution shifts ...
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02/14/2022
Black-Box Generalization
We provide the first generalization error analysis for black-box learnin...
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07/02/2020
Federated Learning with Compression: Unified Analysis and Sharp Guarantees
In federated learning, communication cost is often a critical bottleneck...
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11/12/2019
Efficient Fair Principal Component Analysis
The flourishing assessments of fairness measure in machine learning algo...
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10/31/2019
On the Convergence of Local Descent Methods in Federated Learning
In federated distributed learning, the goal is to optimize a global trai...
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10/30/2019
Local SGD with Periodic Averaging: Tighter Analysis and Adaptive Synchronization
Communication overhead is one of the key challenges that hinders the sca...
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06/15/2018
Straggler-Resilient and Communication-Efficient Distributed Iterative Linear Solver
We propose a novel distributed iterative linear inverse solver method. O...
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01/31/2018
