1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.RO2026
Data-Efficient Hierarchical Goal-Conditioned Reinforcement Learning via Normalizing Flows
Shaswat Garg, Matin Moezzi, Brandon Da Silva
Hierarchical goal-conditioned reinforcement learning (H-GCRL) provides a powerful framework for tackling complex, long-horizon tasks by decomposing them into structured subgoals. H…
cs.LG2023
An Uncertainty-Aware Pseudo-Label Selection Framework using Regularized Conformal Prediction
Matin Moezzi
Consistency regularization-based methods are prevalent in semi-supervised learning (SSL) algorithms due to their exceptional performance. However, they mainly depend on domain-spec…
cs.LG2023★ 1 cited
A Comparison of Classical and Deep Reinforcement Learning Methods for HVAC Control
Marshall Wang, John Willes, Thomas Jiralerspong +1
Reinforcement learning (RL) is a promising approach for optimizing HVAC control. RL offers a framework for improving system performance, reducing energy consumption, and enhancing…