193 citations · 1.1k across the 57 of their papers we have counts for
10 papers · 1 filter
Online Prototype Alignment for Few-shot Policy Transfer
Qi Yi, Rui Zhang, Shaohui Peng +10
Domain adaptation in reinforcement learning (RL) mainly deals with the changes of observation when transferring the policy to a new environment. Many traditional approaches of doma…
Conceptual Reinforcement Learning for Language-Conditioned Tasks
Shaohui Peng, Xing Hu, Rui Zhang +7
Despite the broad application of deep reinforcement learning (RL), transferring and adapting the policy to unseen but similar environments is still a significant challenge. Recentl…
Ultra-low Precision Multiplication-free Training for Deep Neural Networks
Chang Liu, Rui Zhang, Xishan Zhang +5
The training for deep neural networks (DNNs) demands immense energy consumption, which restricts the development of deep learning as well as increases carbon emissions. Thus, the s…
Online Symbolic Regression with Informative Query
Pengwei Jin, Di Huang, Rui Zhang +5
Symbolic regression, the task of extracting mathematical expressions from the observed data $\{ \vx_i, y_i \}$, plays a crucial role in scientific discovery. Despite the promising…
Quantized Distributed Training of Large Models with Convergence Guarantees
Ilia Markov, Adrian Vladu, Qi Guo +1
Communication-reduction techniques are a popular way to improve scalability in data-parallel training of deep neural networks (DNNs). The recent emergence of large language models…
Object-Category Aware Reinforcement Learning
Qi Yi, Rui Zhang, Shaohui Peng +6
Object-oriented reinforcement learning (OORL) is a promising way to improve the sample efficiency and generalization ability over standard RL. Recent works that try to solve OORL t…