More information about my work can be found on [Google Scholar]
Preprints
- Human vs. Generative AI in Content Creation Competition: Symbiosis or Conflict?
Fan Yao, Chuanhao Li, Denis Nekipelov, Hongning Wang, Haifeng Xu
arXiv 2024 [paper]
Publications
Sequential decision making & algorithmic game theory
- Pure Exploration in Asynchronous Federated Bandits
Zichen Wang, Chuanhao Li, Chenyu Song, Lianghui Wang, Quanquan Gu, Huazheng Wang
UAI 2024 [paper] - Incentivized Truthful Communication for Federated Bandits
Zhepei Wei*, Chuanhao Li*, Haifeng Xu, Hongning Wang
ICLR 2024 [paper] - Communication-Efficient Federated Non-Linear Bandit Optimization
Chuanhao Li*, Chong Liu*, Yu-Xiang Wang
ICLR 2024 [paper] - Rethinking Incentives in Recommender Systems: Are Monotone Rewards Always Beneficial?
Fan Yao, Chuanhao Li, Karthik Abinav Sankararaman, Yiming Liao, Yan Zhu, Qifan Wang, Hongning Wang, Haifeng Xu
NeurIPS 2023 [paper] - Incentivized Communication for Federated Bandits
Zhepei Wei*, Chuanhao Li*, Haifeng Xu, Hongning Wang
NeurIPS 2023 [paper] - Incentivizing Exploration in Linear Bandits under Information Gap
Huazheng Wang, Haifeng Xu, Chuanhao Li, Zhiyuan Liu, Hongning Wang
RecSys 2023 [paper] - How Bad is Top-K Recommendation under Competing Content Creators?
Fan Yao, Chuanhao Li, Denis Nekipelov, Hongning Wang, Haifeng Xu
ICML 2023 [paper] - Learning Kernelized Contextual Bandits in a Distributed and Asynchronous Environment
Chuanhao Li, Huazheng Wang, Mengdi Wang, Hongning Wang
ICLR 2023 [paper] - Communication Efficient Distributed Learning for Kernelized Contextual Bandits
Chuanhao Li, Huazheng Wang, Mengdi Wang, Hongning Wang
NeurIPS 2022 [paper] - Communication Efficient Federated Learning for Generalized Linear Bandits
Chuanhao Li, Hongning Wang
NeurIPS 2022 [paper] [code] - Learning from a Learning User for Optimal Recommendations
Fan Yao, Chuanhao Li, Denis Nekipelov, Hongning Wang, Haifeng Xu
ICML 2022 [paper] - Learning the Optimal Recommendation from Explorative Users
Fan Yao, Chuanhao Li, Denis Nekipelov, Hongning Wang, Haifeng Xu
AAAI 2022 [paper] - Asynchronous Upper Confidence Bound Algorithms for Federated Linear Bandits
Chuanhao Li, Hongning Wang
AISTATS 2022 [paper] [code] - When and Whom to Collaborate with in a Changing Environment: A Collaborative Dynamic Bandit Solution
Chuanhao Li, Qingyun Wu, Hongning Wang
SIGIR 2021 [paper] [code] - Unifying Clustered and Non-stationary Bandits
Chuanhao Li, Qingyun Wu, Hongning Wang
AISTATS 2021 [paper] [code]
Applications of deep Learning in vibration signals
- A Deep Convolutional Neural Network with New Training Methods for Bearing Fault Diagnosis under Noisy Environment and Different Working Load
Wei Zhang, Chuanhao Li, Gaoliang Peng, Yuanhang Chen, Zhujun Zhang
Mechanical Systems and Signal Processing 2018 [paper] - ACDIN: Bridging the Gap between Artificial and Real Bearing Damages for Bearing Fault Diagnosis
Yuanhang Chen, Gaoliang Peng, Chaohao Xie, Wei Zhang, Chuanhao Li, Shaohui Liu
Neurocomputing 2018 [paper] - Bearing Fault Diagnosis Using Fully-connected Winner-take-all Autoencoder
Chuanhao Li, Wei Zhang, Gaoliang Peng, Shaohui Liu
IEEE Access 2017 [paper] [code] - A New Deep Learning Model for Fault Diagnosis with Good Anti-noise and Domain Adaptation Ability on Raw Vibration Signals
Wei Zhang, Gaoliang Peng, Chuanhao Li, Yuanhang Chen, Zhujun Zhang
Sensors 2017 [paper] - Rolling Element Bearings Fault Intelligent Diagnosis Based on Convolutional Neural Networks using Raw Sensing Signal
Wei Zhang, Gaoliang Peng, Chuanhao Li
IIH-MSP 2016 [paper] - Bearings Fault Diagnosis based on Convolutional Neural Networks with 2-D Representation of Vibration Signals as Input
Wei Zhang, Gaoliang Peng, Chuanhao Li
ICMME 2016 [paper]