activity
20182026
most citedData-Free Adversarial Distillation

103 citations · 497 across the 44 of their papers we have counts for

collaborators
Showing 2023Show all

8 papers · 1 filter

cs.AI2023

Agent-Aware Training for Agent-Agnostic Action Advising in Deep Reinforcement Learning

Yaoquan Wei, Shunyu Liu, Jie Song +4

Action advising endeavors to leverage supplementary guidance from expert teachers to alleviate the issue of sampling inefficiency in Deep Reinforcement Learning (DRL). Previous age…

cs.LG2023

ModelGiF: Gradient Fields for Model Functional Distance

Jie Song, Zhengqi Xu, Sai Wu +2

The last decade has witnessed the success of deep learning and the surge of publicly released trained models, which necessitates the quantification of the model functional distance…

cs.CV2023★ 2 cited

Lookaround Optimizer: steps around, 1 step average

Jiangtao Zhang, Shunyu Liu, Jie Song +3

Weight Average (WA) is an active research topic due to its simplicity in ensembling deep networks and the effectiveness in promoting generalization. Existing weight average approac…

cs.AI2023★ 13 cited

Is Centralized Training with Decentralized Execution Framework Centralized Enough for MARL?

Yihe Zhou, Shunyu Liu, Yunpeng Qing +4

Centralized Training with Decentralized Execution (CTDE) has recently emerged as a popular framework for cooperative Multi-Agent Reinforcement Learning (MARL), where agents can use…

cs.LG2023★ 20 cited

Temporal Aggregation and Propagation Graph Neural Networks for Dynamic Representation

Tongya Zheng, Xinchao Wang, Zunlei Feng +6

Temporal graphs exhibit dynamic interactions between nodes over continuous time, whose topologies evolve with time elapsing. The whole temporal neighborhood of nodes reveals the va…

cs.CV2023★ 2 cited

Generalization Matters: Loss Minima Flattening via Parameter Hybridization for Efficient Online Knowledge Distillation

Tianli Zhang, Mengqi Xue, Jiangtao Zhang +5

Most existing online knowledge distillation(OKD) techniques typically require sophisticated modules to produce diverse knowledge for improving students' generalization ability. In…