242 citations · 1.2k across the 37 of their papers we have counts for
6 papers · 1 filter
Federated Variance-Reduced Stochastic Gradient Descent with Robustness to Byzantine Attacks
Zhaoxian Wu, Qing Ling, Tianyi Chen +1
This paper deals with distributed finite-sum optimization for learning over networks in the presence of malicious Byzantine attacks. To cope with such attacks, most resilient appro…
Communication-Efficient Distributed Learning via Lazily Aggregated Quantized Gradients
Jun Sun, Tianyi Chen, Georgios B. Giannakis +1
The present paper develops a novel aggregated gradient approach for distributed machine learning that adaptively compresses the gradient communication. The key idea is to first qua…
Decentralized Markov Chain Gradient Descent
Tao Sun, Dongsheng Li
Decentralized stochastic gradient method emerges as a promising solution for solving large-scale machine learning problems. This paper studies the decentralized Markov chain gradie…
Communication-Censored Distributed Stochastic Gradient Descent
Weiyu Li, Tianyi Chen, Liping Li +2
This paper develops a communication-efficient algorithm to solve the stochastic optimization problem defined over a distributed network, aiming at reducing the burdensome communica…
Generative Adversarial Network for Handwritten Text
Bo Ji, Tianyi Chen
Generative adversarial networks (GANs) have proven hugely successful in variety of applications of image processing. However, generative adversarial networks for handwriting is rel…
Novel Dense Subgraph Discovery Primitives: Risk Aversion and Exclusion Queries
Charalampos E. Tsourakakis, Tianyi Chen, Naonori Kakimura +1
In the densest subgraph problem, given a weighted undirected graph , with non-negative edge weights, we are asked to find a subset of nodes that maximizes…