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02/14/2023
EPISODE: Episodic Gradient Clipping with Periodic Resampled Corrections for Federated Learning with Heterogeneous Data
Gradient clipping is an important technique for deep neural networks wit...
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11/15/2022
On Inferring User Socioeconomic Status with Mobility Records
When users move in a physical space (e.g., an urban space), they would h...
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07/17/2022
Fast Composite Optimization and Statistical Recovery in Federated Learning
As a prevalent distributed learning paradigm, Federated Learning (FL) tr...
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05/27/2022
Will Bilevel Optimizers Benefit from Loops
Bilevel optimization has arisen as a powerful tool for solving a variety...
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05/10/2022
A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks
In distributed training of deep neural networks or Federated Learning (F...
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10/21/2021
Asynchronous Decentralized Distributed Training of Acoustic Models
Large-scale distributed training of deep acoustic models plays an import...
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05/05/2020
Communication-Efficient Distributed Stochastic AUC Maximization with Deep Neural Networks
In this paper, we study distributed algorithms for large-scale AUC maxim...
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02/04/2020
Improving Efficiency in Large-Scale Decentralized Distributed Training
Decentralized Parallel SGD (D-PSGD) and its asynchronous variant Asynchr...
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01/27/2020
The game of Cops and Robbers on directed graphs with forbidden subgraphs
The traditional game of cops and robbers is played on undirected graph. ...
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12/26/2019
Towards Better Understanding of Adaptive Gradient Algorithms in Generative Adversarial Nets
Adaptive gradient algorithms perform gradient-based updates using the hi...
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10/28/2019
Decentralized Parallel Algorithm for Training Generative Adversarial Nets
Generative Adversarial Networks (GANs) are powerful class of generative ...
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09/25/2019
Learning with Long-term Remembering: Following the Lead of Mixed Stochastic Gradient
Current deep neural networks can achieve remarkable performance on a sin...
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08/29/2019
The Cop Number of Graphs with Forbidden Induced Subgraphs
In the game of Cops and Robber, a team of cops attempts to capture a rob...
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08/28/2019
Stochastic AUC Maximization with Deep Neural Networks
Stochastic AUC maximization has garnered an increasing interest due to b...
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10/24/2018
Solving Weakly-Convex-Weakly-Concave Saddle-Point Problems as Weakly-Monotone Variational Inequality
In this paper, we consider first-order algorithms for solving a class of...
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10/04/2018
Non-Convex Min-Max Optimization: Provable Algorithms and Applications in Machine Learning
Min-max saddle-point problems have broad applications in many tasks in m...
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05/11/2018
Fast Rates of ERM and Stochastic Approximation: Adaptive to Error Bound Conditions
Error bound conditions (EBC) are properties that characterize the growth...
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10/25/2017
Stochastic Non-convex Optimization with Strong High Probability Second-order Convergence
In this paper, we study stochastic non-convex optimization with non-conv...
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09/25/2017