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02/08/2023
DIFF2: Differential Private Optimization via Gradient Differences for Nonconvex Distributed Learning
Differential private optimization for nonconvex smooth objective is cons...
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09/01/2022
Versatile Single-Loop Method for Gradient Estimator: First and Second Order Optimality, and its Application to Federated Learning
While variance reduction methods have shown great success in solving lar...
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02/12/2022
Escaping Saddle Points with Bias-Variance Reduced Local Perturbed SGD for Communication Efficient Nonconvex Distributed Learning
In recent centralized nonconvex distributed learning and federated learn...
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02/05/2021
Bias-Variance Reduced Local SGD for Less Heterogeneous Federated Learning
Federated learning is one of the important learning scenarios in distrib...
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06/19/2020
Gradient Descent in RKHS with Importance Labeling
Labeling cost is often expensive and is a fundamental limitation of supe...
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05/29/2019
Accelerated Sparsified SGD with Error Feedback
We study a stochastic gradient method for synchronous distributed optimi...
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09/05/2018
Sample Efficient Stochastic Gradient Iterative Hard Thresholding Method for Stochastic Sparse Linear Regression with Limited Attribute Observation
We develop new stochastic gradient methods for efficiently solving spars...
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08/26/2018
Spectral-Pruning: Compressing deep neural network via spectral analysis
The model size of deep neural network is getting larger and larger to re...
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03/01/2017
Doubly Accelerated Stochastic Variance Reduced Dual Averaging Method for Regularized Empirical Risk Minimization
In this paper, we develop a new accelerated stochastic gradient method f...
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03/08/2016