1 citations · 1 across the 1 of their papers we have counts for
4 papers
Privacy-Preserving Self-Taught Federated Learning for Heterogeneous Data
Kai-Fung Chu, Lintao Zhang
Many application scenarios call for training a machine learning model among multiple participants. Federated learning (FL) was proposed to enable joint training of a deep learning…
OpEvo: An Evolutionary Method for Tensor Operator Optimization
Xiaotian Gao, Cui Wei, Lintao Zhang +1
Training and inference efficiency of deep neural networks highly rely on the performance of tensor operators on hardware platforms. Manually optimizing tensor operators has limitat…
RPC Considered Harmful: Fast Distributed Deep Learning on RDMA
Jilong Xue, Youshan Miao, Cheng Chen +3
Deep learning emerges as an important new resource-intensive workload and has been successfully applied in computer vision, speech, natural language processing, and so on. Distribu…
Episodic Memory Deep Q-Networks
Zichuan Lin, Tianqi Zhao, Guangwen Yang +1
Reinforcement learning (RL) algorithms have made huge progress in recent years by leveraging the power of deep neural networks (DNN). Despite the success, deep RL algorithms are kn…