Haipeng Chen

According to our database, Haipeng Chen authored at least 35 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Decentralized Online Learning in General-Sum Stackelberg Games.

Yaolong Yu, Haipeng Chen

CoRR, 2024

S²AC: Energy-Based Reinforcement Learning with Stein Soft Actor Critic.

Safa Messaoud, Billel Mokeddem, Zhenghai Xue, Linsey Pang, Bo An, Haipeng Chen, Sanjay Chawla

CoRR, 2024

S2AC: Energy-Based Reinforcement Learning with Stein Soft Actor Critic.

Safa Messaoud, Billel Mokeddem, Zhenghai Xue, Linsey Pang, Bo An, Haipeng Chen, Sanjay Chawla

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Towards Real-Time and Personalized Code Generation.

Han Xu, Xingyuan Wang, Haipeng Chen

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023

Predicting micronutrient deficiency with publicly available satellite data.

Elizabeth Bondi-Kelly, Haipeng Chen, Christopher D. Golden, Nikhil Behari, Milind Tambe

AI Mag., March, 2023

M2P2: Multimodal Persuasion Prediction Using Adaptive Fusion.

Chongyang Bai, Haipeng Chen, Srijan Kumar, Jure Leskovec, V. S. Subrahmanian

IEEE Trans. Multim., 2023

Complex Contagion Influence Maximization: A Reinforcement Learning Approach.

Haipeng Chen, Bryan Wilder, Wei Qiu, Bo An, Eric Rice, Milind Tambe

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

AI-driven Prices for Externalities and Sustainability in Production Markets.

Panayiotis Danassis, Aris Filos-Ratsikas, Haipeng Chen, Milind Tambe, Boi Faltings

Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

A Learning Approach to Complex Contagion Influence Maximization.

Haipeng Chen, Bryan Wilder, Wei Qiu, Bo An, Eric Rice, Milind Tambe

Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

2022

PCAM: A Data-driven Probabilistic Cyber-alert Management Framework.

Haipeng Chen, Andrew Duncklee, Sushil Jajodia, Rui Liu, Sean R. McNamara, V. S. Subrahmanian

ACM Trans. Internet Techn., 2022

Learning Correlated Stackelberg Equilibrium in General-Sum Multi-Leader-Single-Follower Games.

Yaolong Yu, Haifeng Xu, Haipeng Chen

CoRR, 2022

Sequential Vaccine Allocation with Delayed Feedback.

Yichen Xiao, Han-Ching Ou, Haipeng Chen, Van Thieu Nguyen, Long Tran-Thanh

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Micronutrient Deficiency Prediction via Publicly Available Satellite Data.

Elizabeth Bondi, Haipeng Chen, Christopher D. Golden, Nikhil Behari, Milind Tambe

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Using Public Data to Predict Demand for Mobile Health Clinics.

Haipeng Chen, Susobhan Ghosh, Gregory Fan, Nikhil Behari, Arpita Biswas, Mollie Williams, Nancy E. Oriol, Milind Tambe

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Using Word Embeddings to Deter Intellectual Property Theft through Automated Generation of Fake Documents.

Almas Abdibayev, Dongkai Chen, Haipeng Chen, Deepti Poluru, V. S. Subrahmanian

ACM Trans. Manag. Inf. Syst., 2021

Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Problems by Reinforcement Learning.

Kai Wang, Sanket Shah, Haipeng Chen, Andrew Perrault, Finale Doshi-Velez, Milind Tambe

CoRR, 2021

Robust reinforcement learning under minimax regret for green security.

Lily Xu, Andrew Perrault, Fei Fang, Haipeng Chen, Milind Tambe

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Contingency-aware influence maximization: A reinforcement learning approach.

Haipeng Chen, Wei Qiu, Han-Ching Ou, Bo An, Milind Tambe

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Making by Reinforcement Learning.

Kai Wang, Sanket Shah, Haipeng Chen, Andrew Perrault, Finale Doshi-Velez, Milind Tambe

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Active Screening for Recurrent Diseases: A Reinforcement Learning Approach.

Han-Ching Ou, Haipeng Chen, Shahin Jabbari, Milind Tambe

Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

2020

PIE: A Data-Driven Payoff Inference Engine for Strategic Security Applications.

Haipeng Chen, Mohammad Taghi Hajiaghayi, Sarit Kraus, Anshul Sawant, Edoardo Serra, V. S. Subrahmanian, Yanhai Xiong

IEEE Trans. Comput. Soc. Syst., 2020

Disclose or Exploit? A Game-Theoretic Approach to Strategic Decision Making in Cyber-Warfare.

Haipeng Chen, Qian Han, Sushil Jajodia, Roy Lindelauf, V. S. Subrahmanian, Yanhai Xiong

IEEE Syst. J., 2020

Learning Behaviors with Uncertain Human Feedback.

Xu He, Haipeng Chen, Bo An

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Robust Lock-Down Optimization for COVID-19 Policy Guidance.

Ankit Bhardwaj, Han-Ching Ou, Haipeng Chen, Shahin Jabbari, Milind Tambe, Rahul Panicker, Alpan Raval

Proceedings of the AAAI Fall Symposium on AI for Social Good, 2020

2019

Using Twitter to Predict When Vulnerabilities will be Exploited.

Haipeng Chen, Rui Liu, Noseong Park, V. S. Subrahmanian

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Dynamic Electronic Toll Collection via Multi-Agent Deep Reinforcement Learning with Edge-Based Graph Convolutional Networks.

Wei Qiu, Haipeng Chen, Bo An

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

VEST: A System for Vulnerability Exploit Scoring & Timing.

Haipeng Chen, Jing Liu, Rui Liu, Noseong Park, V. S. Subrahmanian

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

FakeTables: Using GANs to Generate Functional Dependency Preserving Tables with Bounded Real Data.

Haipeng Chen, Sushil Jajodia, Jing Liu, Noseong Park, Vadim Sokolov, V. S. Subrahmanian

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

InBEDE: Integrating Contextual Bandit with TD Learning for Joint Pricing and Dispatch of Ride-Hailing Platforms.

Haipeng Chen, Yan Jiao, Zhiwei (Tony) Qin, Xiaocheng Tang, Hao Li, Bo An, Hongtu Zhu, Jieping Ye

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

VASE: A Twitter-Based Vulnerability Analysis and Score Engine.

Haipeng Chen, Jing Liu, Rui Liu, Noseong Park, V. S. Subrahmanian

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

2018

HogRider: Champion Agent of Microsoft Malmo Collaborative AI Challenge.

Yanhai Xiong, Haipeng Chen, Mengchen Zhao, Bo An

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

DyETC: Dynamic Electronic Toll Collection for Traffic Congestion Alleviation.

Haipeng Chen, Bo An, Guni Sharon, Josiah P. Hanna, Peter Stone, Chunyan Miao, Yeng Chai Soh

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Data-Driven Frequency-Based Airline Profit Maximization.

Bo An, Haipeng Chen, Noseong Park, V. S. Subrahmanian

ACM Trans. Intell. Syst. Technol., 2017

Workload Factoring and Resource Sharing via Joint Vertical and Horizontal Cloud Federation Networks.

Haipeng Chen, Bo An, Dusit Niyato, Yeng Chai Soh, Chunyan Miao

IEEE J. Sel. Areas Commun., 2017

2016

MAP: Frequency-Based Maximization of Airline Profits based on an Ensemble Forecasting Approach.

Bo An, Haipeng Chen, Noseong Park, V. S. Subrahmanian

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016