48 citations · 288 across the 47 of their papers we have counts for
5 papers · 1 filter
Offline Reinforcement Learning with Reverse Model-based Imagination
Jianhao Wang, Wenzhe Li, Haozhe Jiang +3
In offline reinforcement learning (offline RL), one of the main challenges is to deal with the distributional shift between the learning policy and the given dataset. To address th…
Boosting Discriminative Visual Representation Learning with Scenario-Agnostic Mixup
Siyuan Li, Zicheng Liu, Zedong Wang +3
Mixup is a well-known data-dependent augmentation technique for DNNs, consisting of two sub-tasks: mixup generation and classification. However, the recent dominant online training…
Exploring Localization for Self-supervised Fine-grained Contrastive Learning
Di Wu, Siyuan Li, Zelin Zang +1
Self-supervised contrastive learning has demonstrated great potential in learning visual representations. Despite their success in various downstream tasks such as image classifica…
Active Hierarchical Exploration with Stable Subgoal Representation Learning
Siyuan Li, Jin Zhang, Jianhao Wang +2
Goal-conditioned hierarchical reinforcement learning (GCHRL) provides a promising approach to solving long-horizon tasks. Recently, its success has been extended to more general se…
AutoMix: Unveiling the Power of Mixup for Stronger Classifiers
Zicheng Liu, Siyuan Li, Di Wu +4
Data mixing augmentation have proved to be effective in improving the generalization ability of deep neural networks. While early methods mix samples by hand-crafted policies (e.g.…