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08/28/2023
On the Tradeoff between Privacy Preservation and Byzantine-Robustness in Decentralized Learning
This paper jointly considers privacy preservation and Byzantine-robustne...
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08/10/2023
Byzantine-Robust Decentralized Stochastic Optimization with Stochastic Gradient Noise-Independent Learning Error
This paper studies Byzantine-robust stochastic optimization over a decen...
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07/16/2023
Byzantine-Robust Distributed Online Learning: Taming Adversarial Participants in An Adversarial Environment
This paper studies distributed online learning under Byzantine attacks. ...
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04/08/2023
SAR2EO: A High-resolution Image Translation Framework with Denoising Enhancement
Synthetic Aperture Radar (SAR) to electro-optical (EO) image translation...
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11/20/2022
Spectral Adversarial Training for Robust Graph Neural Network
Recent studies demonstrate that Graph Neural Networks (GNNs) are vulnera...
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06/14/2022
Lazy Queries Can Reduce Variance in Zeroth-order Optimization
A major challenge of applying zeroth-order (ZO) methods is the high quer...
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06/09/2022
Byzantine-Resilient Decentralized Stochastic Optimization with Robust Aggregation Rules
This work focuses on decentralized stochastic optimization in the presen...
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05/30/2022
Confederated Learning: Federated Learning with Decentralized Edge Servers
Federated learning (FL) is an emerging machine learning paradigm that al...
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04/29/2022
Bridging Differential Privacy and Byzantine-Robustness via Model Aggregation
This paper aims at jointly addressing two seemly conflicting issues in f...
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01/19/2022
Variance-Reduced Stochastic Quasi-Newton Methods for Decentralized Learning: Part I
In this work, we investigate stochastic quasi-Newton methods for minimiz...
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06/13/2021
Stochastic Alternating Direction Method of Multipliers for Byzantine-Robust Distributed Learning
This paper aims to solve a distributed learning problem under Byzantine ...
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04/14/2021
BROADCAST: Reducing Both Stochastic and Compression Noise to Robustify Communication-Efficient Federated Learning
Communication between workers and the master node to collect local stoch...
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09/17/2020
Byzantine-Robust Variance-Reduced Federated Learning over Distributed Non-i.i.d. Data
We propose a Byzantine-robust variance-reduced stochastic gradient desce...
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05/12/2020
Byzantine-Robust Decentralized Stochastic Optimization over Static and Time-Varying Networks
In this paper, we consider the Byzantine-robust stochastic optimization ...
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04/30/2020
Conditional Augmentation for Aspect Term Extraction via Masked Sequence-to-Sequence Generation
Aspect term extraction aims to extract aspect terms from review texts as...
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03/22/2020
HierTrain: Fast Hierarchical Edge AI Learning with Hybrid Parallelism in Mobile-Edge-Cloud Computing
Nowadays, deep neural networks (DNNs) are the core enablers for many eme...
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12/29/2019
Federated Variance-Reduced Stochastic Gradient Descent with Robustness to Byzantine Attacks
This paper deals with distributed finite-sum optimization for learning o...
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10/19/2019
Convolutional Neural Networks for Space-Time Block Coding Recognition
We find that the latest advances in machine learning with deep neural ne...
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09/15/2019
Communication-Censored Linearized ADMM for Decentralized Consensus Optimization
In this paper, we propose a communication- and computation-efficient alg...
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09/09/2019
Communication-Censored Distributed Stochastic Gradient Descent
This paper develops a communication-efficient algorithm to solve the sto...
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11/15/2018
Asynchronous Stochastic Composition Optimization with Variance Reduction
Composition optimization has drawn a lot of attention in a wide variety ...
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11/09/2018
RSA: Byzantine-Robust Stochastic Aggregation Methods for Distributed Learning from Heterogeneous Datasets
In this paper, we propose a class of robust stochastic subgradient metho...
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09/05/2018
Solving Non-smooth Constrained Programs with Lower Complexity than O(1/ε): A Primal-Dual Homotopy Smoothing Approach
We propose a new primal-dual homotopy smoothing algorithm for a linearly...
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08/29/2018
DADA: Deep Adversarial Data Augmentation for Extremely Low Data Regime Classification
Deep learning has revolutionized the performance of classification, but ...
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01/14/2017
An Online Convex Optimization Approach to Dynamic Network Resource Allocation
Existing approaches to online convex optimization (OCO) make sequential ...
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08/14/2016
Stacked Approximated Regression Machine: A Simple Deep Learning Approach
With the agreement of my coauthors, I Zhangyang Wang would like to withd...
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05/21/2016
Make Workers Work Harder: Decoupled Asynchronous Proximal Stochastic Gradient Descent
Asynchronous parallel optimization algorithms for solving large-scale ma...
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04/06/2016
Learning A Deep ℓ_∞ Encoder for Hashing
We investigate the ℓ_∞-constrained representation which demonstrates rob...
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01/16/2016
D^3: Deep Dual-Domain Based Fast Restoration of JPEG-Compressed Images
In this paper, we design a Deep Dual-Domain (D^3) based fast restoration...
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09/01/2015
Learning Deep ℓ_0 Encoders
Despite its nonconvex nature, ℓ_0 sparse approximation is desirable in m...
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03/30/2015