2 citations · 2 across the 6 of their papers we have counts for
4 papers · 1 filter
ELEMENT: Episodic and Lifelong Exploration via Maximum Entropy
Hongming Li, Zhao Yang, Shujian Yu +3
Reinforcement learning agents depend on reward signals whose density is rarely under the designer's control, and when such signals are absent, an agent must generate its own drive…
Generalized Cauchy-Schwarz Divergence and Its Deep Learning Applications
Mingfei Lu, Chenxu Li, Shujian Yu +2
Divergence measures play a central role and become increasingly essential in deep learning, yet efficient measures for multiple (more than two) distributions are rarely explored. T…
Domain Adaptation with Cauchy-Schwarz Divergence
Wenzhe Yin, Shujian Yu, Yicong Lin +3
Domain adaptation aims to use training data from one or multiple source domains to learn a hypothesis that can be generalized to a different, but related, target domain. As such, h…
Cauchy-Schwarz Divergence Information Bottleneck for Regression
Shujian Yu, Xi Yu, Sigurd Løkse +2
The information bottleneck (IB) approach is popular to improve the generalization, robustness and explainability of deep neural networks. Essentially, it aims to find a minimum suf…