1 citations · 1 across the 10 of their papers we have counts for
6 papers · 1 filter
TabQL: In-Context Q-Learning with Tabular Foundation Models
Qisai Liu, Zhanhong Jiang, Timilehin Ayanlade +4
We propose Tabular Q-Learning (TabQL), a reinforcement learning framework that replaces the conventional parametric Q-network in Deep Q-Learning (DQN) with a tabular foundation mod…
COOPO: Cyclic Offline-Online Policy Optimization Algorithm
Qisai Liu, Zhanhong Jiang, Joshua Russell Waite +3
Offline reinforcement learning struggles with distributional shift and constrained performance due to static dataset limitations, while online RL demands prohibitive environment in…
LexiSafe: Offline Safe Reinforcement Learning with Lexicographic Safety-Reward Hierarchy
Hsin-Jung Yang, Zhanhong Jiang, Prajwal Koirala +3
Offline safe reinforcement learning (RL) is increasingly important for cyber-physical systems (CPS), where safety violations during training are unacceptable and only pre-collected…
Bidirectional Linear Recurrent Models for Sequence-Level Multisource Fusion
Qisai Liu, Zhanhong Jiang, Joshua R. Waite +3
Sequence modeling is a critical yet challenging task with wide-ranging applications, especially in time series forecasting for domains like weather prediction, temperature monitori…
Enhancing PPO with Trajectory-Aware Hybrid Policies
Qisai Liu, Zhanhong Jiang, Hsin-Jung Yang +3
Proximal policy optimization (PPO) is one of the most popular state-of-the-art on-policy algorithms that has become a standard baseline in modern reinforcement learning with applic…
A Deep Learning Approach to Detect Lean Blowout in Combustion Systems
Tryambak Gangopadhyay, Somnath De, Qisai Liu +3
Lean combustion is environment friendly with low NOx emissions and also provides better fuel efficiency in a combustion system. However, approaching towards lean combustion can mak…