145 citations · 555 across the 30 of their papers we have counts for
Showing cs.LGShow all
3 papers · 1 filter
cs.LG2022★ 1 cited
Accelerating Dataset Distillation via Model Augmentation
Lei Zhang, Jie Zhang, Bowen Lei +6
Dataset Distillation (DD), a newly emerging field, aims at generating much smaller but efficient synthetic training datasets from large ones. Existing DD methods based on gradient…
cs.LG2022
Hierarchical Estimation for Effective and Efficient Sampling Graph Neural Network
Yang Li, Bingbing Xu, Qi Cao +2
Improving the scalability of GNNs is critical for large graphs. Existing methods leverage three sampling paradigms including node-wise, layer-wise and subgraph sampling, then desig…
cs.LG2019
Proximal Policy Optimization with Mixed Distributed Training
Zhenyu Zhang, Xiangfeng Luo, Tong Liu +5
Instability and slowness are two main problems in deep reinforcement learning. Even if proximal policy optimization (PPO) is the state of the art, it still suffers from these two p…