Feng, Lu

13 publications

UAI 2025 Adaptive Reward Design for Reinforcement Learning Minjae Kwon, Ingy ElSayed-Aly, Lu Feng

IJCAI 2025 Counterfactual Explanations for Continuous Action Reinforcement Learning Shuyang Dong, Shangtong Zhang, Lu Feng

AAAI 2025 Quantitative Predictive Monitoring and Control for Safe Human-Machine Interaction Shuyang Dong, Meiyi Ma, Josephine Lamp, Sebastian G. Elbaum, Matthew B. Dwyer, Lu Feng

AAAI 2025 Towards Computational Foreseeability Sarit Kraus, Kayla Boggess, Robert Kim, Bryan H. Choi, Lu Feng

AAAI 2024 ACAMDA: Improving Data Efficiency in Reinforcement Learning Through Guided Counterfactual Data Augmentation Yuewen Sun, Erli Wang, Biwei Huang, Chaochao Lu, Lu Feng, Changyin Sun, Kun Zhang

IJCAI 2024 ADESSE: Advice Explanations in Complex Repeated Decision-Making Environments Sören Schleibaum, Lu Feng, Sarit Kraus, Jörg P. Müller

IJCAI 2023 Explainable Multi-Agent Reinforcement Learning for Temporal Queries Kayla Boggess, Sarit Kraus, Lu Feng

NeurIPS 2023 GlucoSynth: Generating Differentially-Private Synthetic Glucose Traces Josephine Lamp, Mark Derdzinski, Christopher Hannemann, Joost van der Linden, Lu Feng, Tianhao Wang, David Evans

IJCAI 2022 Toward Policy Explanations for Multi-Agent Reinforcement Learning Kayla Boggess, Sarit Kraus, Lu Feng

ICCV 2021 MEDIRL: Predicting the Visual Attention of Drivers via Maximum Entropy Deep Inverse Reinforcement Learning Sonia Baee, Erfan Pakdamanian, Inki Kim, Lu Feng, Vicente Ordonez, Laura Barnes

NeurIPS 2020 STLnet: Signal Temporal Logic Enforced Multivariate Recurrent Neural Networks Meiyi Ma, Ji Gao, Lu Feng, John Stankovic

IJCAI 2018 Mixed Causal Structure Discovery with Application to Prescriptive Pricing Wenjuan Wei, Lu Feng, Chunchen Liu

ICML 2015 Scalable Model Selection for Large-Scale Factorial Relational Models Chunchen Liu, Lu Feng, Ryohei Fujimaki, Yusuke Muraoka