2 citations · 2 across the 9 of their papers we have counts for
Showing cs.LGShow all
3 papers · 1 filter
cs.LG2026
Active Asymmetric Multi-Agent Multimodal Learning under Uncertainty
Rui Liu, Pratap Tokekar, Ming Lin
Multi-agent systems are increasingly equipped with heterogeneous multimodal sensors, enabling richer perception but introducing modality-specific and agent-dependent uncertainty. E…
cs.LG2025
Adaptive Conformal Guidance for Learning under Uncertainty
Rui Liu, Peng Gao, Yu Shen +2
Learning with guidance has proven effective across a wide range of machine learning systems. Guidance may, for example, come from annotated datasets in supervised learning, pseudo-…
cs.LG2024
Towards Efficient Risk-Sensitive Policy Gradient: An Iteration Complexity Analysis
Rui Liu, Anish Gupta, Erfaun Noorani +1
Reinforcement Learning (RL) has shown exceptional performance across various applications, enabling autonomous agents to learn optimal policies through interaction with their envir…