Larkin Liu

13 papers A* 1Journal 10Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Riemannian Manifold Learning for Stackelberg Games with Neural Flow Representations. AAAI Larkin Liu, Kashif Rasul, Yutong Chao, Jalal Etesami
2025	J	`jnl`	Online Mixture of Experts: No-Regret Learning for Optimal Collective Decision-Making. CoRR Larkin Liu, Jalal Etesami
2025	J	`jnl`	Riemannian Manifold Learning for Stackelberg Games with Neural Flow Representations. CoRR Larkin Liu, Kashif Rasul, Yutong Chao, Jalal Etesami
2024	J	`jnl`	A Stackelberg Regret Minimizing Framework for Online Learning in Newsvendor Pricing Games. CoRR Larkin Liu, Yuming Rong
2024	—	`conf`	Approximate Nash Equilibrium Learning for n-Player Markov Games in Dynamic Pricing. EPIA (1) Larkin Liu
2024	—	`conf`	Dual-Sourcing via Dynamic Programming with Monte Carlo Value Approximation. ICSTCC Larkin Liu
2024	J	`jnl`	Monte Carlo Planning for Stochastic Control on Constrained Markov Decision Processes. CoRR Larkin Liu, Shiqi Liu, Matej Jusup
2024	J	`jnl`	Optimizing Stochastic Control through State TransitionSeparability and Resource-Utility Exchange. SIGMETRICS Perform. Evaluation Rev. Larkin Liu, Shiqi Liu, Matej Jusup
2022	J	`jnl`	Approximate Nash Equilibrium Learning for n-Player Markov Games in Dynamic Pricing. CoRR Larkin Liu
2022	J	`jnl`	mctreesearch4j: A Monte Carlo Tree Search Implementation for the JVM. J. Open Source Softw. Larkin Liu, Jun Tao Luo
2021	J	`jnl`	An Extensible and Modular Design and Implementation of Monte Carlo Tree Search for the JVM. CoRR Larkin Liu, Jun Tao Luo
2019	J	`jnl`	Improving the Performance of the LSTM and HMM Models via Hybridization. CoRR Larkin Liu, Yu-Chung Lin, Joshua Reid
2019	J	`jnl`	Multi-Armed Bandit Strategies for Non-Stationary Reward Distributions and Delayed Feedback Processes. CoRR Larkin Liu, Richard Downe, Joshua Reid