Multi-Armed Bandit Strategies for Non-Stationary Reward Distributions and Delayed Feedback Processes. - Larkin Liu; Richard Downe; Joshua Reid (CoRR, 2019)

Improving the Performance of the LSTM and HMM Models via Hybridization. - Larkin Liu; Yu-Chung Lin; Joshua Reid (CoRR, 2019)

An Extensible and Modular Design and Implementation of Monte Carlo Tree Search for the JVM. - Larkin Liu; Jun Tao Luo (CoRR, 2021)

mctreesearch4j: A Monte Carlo Tree Search Implementation for the JVM. - Larkin Liu; Jun Tao Luo (J. Open Source Softw., 2022)

Approximate Nash Equilibrium Learning for n-Player Markov Games in Dynamic Pricing. - Larkin Liu (EPIA (1), 2024)

Dual-Sourcing via Dynamic Programming with Monte Carlo Value Approximation. - Larkin Liu (ICSTCC, 2024)

A Stackelberg Regret Minimizing Framework for Online Learning in Newsvendor Pricing Games. - Larkin Liu; Yuming Rong (CoRR, 2024)

Monte Carlo Planning for Stochastic Control on Constrained Markov Decision Processes. - Larkin Liu; Shiqi Liu; Matej Jusup (CoRR, 2024)

Optimizing Stochastic Control through State TransitionSeparability and Resource-Utility Exchange. - Larkin Liu; Shiqi Liu; Matej Jusup (SIGMETRICS Perform. Evaluation Rev., 2024)

Riemannian Manifold Learning for Stackelberg Games with Neural Flow Representations. - Larkin Liu; Kashif Rasul; Yutong Chao; Jalal Etesami (CoRR, 2025)