2 citations · 2 across the 11 of their papers we have counts for
5 papers · 1 filter
DEFlow: Deep Equilibrium Flow Maximum-Entropy Reinforcement Learning
Ruslan Ageev, Huaze Tang, Runqing Miao +2
Expressive flow policies can represent multiple high-value actions, but sampling them with few integration steps while retaining tractable action densities remains challenging. We…
Function-Space Empirical Bayes Regularisation with Large Vision-Language Model Priors
Pengcheng Hao, Huaze Tang, Ercan Engin Kuruoglu +1
Bayesian deep learning (BDL) provides a principled framework for reliable uncertainty quantification by combining deep neural networks with Bayesian inference. A central challenge…
Reinforced Domain Selection for Continuous Domain Adaptation
Hanbing Liu, Huaze Tang, Yanru Wu +2
Continuous Domain Adaptation (CDA) effectively bridges significant domain shifts by progressively adapting from the source domain through intermediate domains to the target domain.…
Bidirectional Soft Actor-Critic: Leveraging Forward and Reverse KL Divergence for Efficient Reinforcement Learning
Yixian Zhang, Huaze Tang, Changxu Wei +1
The Soft Actor-Critic (SAC) algorithm, a state-of-the-art method in maximum entropy reinforcement learning, traditionally relies on minimizing reverse Kullback-Leibler (KL) diverge…
Policy Newton Algorithm in Reproducing Kernel Hilbert Space
Yixian Zhang, Huaze Tang, Chao Wang +1
Reinforcement learning (RL) policies represented in Reproducing Kernel Hilbert Spaces (RKHS) offer powerful representational capabilities. While second-order optimization methods l…