Chen Chen

According to our database, Chen Chen authored at least 25 papers between 2015 and 2025.

Collaborative distances:

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

2025

AttentionPredictor: Temporal Pattern Matters for Efficient LLM Inference.

Qingyue Yang, Jie Wang, Xing Li, Zhihai Wang, Chen Chen, Lei Chen, Xianzhi Yu, Wulong Liu, Jianye Hao, Mingxuan Yuan, Bin Li

CoRR, February, 2025

Hierarchical task network-enhanced multi-agent reinforcement learning: Toward efficient cooperative strategies.

Xuechen Mu, Hankz Hankui Zhuo, Chen Chen, Kai Zhang, Chao Yu, Jianye Hao

Neural Networks, 2025

2024

The Ladder in Chaos: Improving Policy Learning by Harnessing the Parameter Evolving Path in A Low-dimensional Space.

Hongyao Tang, Min Zhang, Chen Chen, Jianye Hao

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Hierarchical Task Network Planning for Facilitating Cooperative Multi-Agent Reinforcement Learning.

Xuechen Mu, Hankz Hankui Zhuo, Chen Chen, Kai Zhang, Chao Yu, Jianye Hao

CoRR, 2023

Dynamic Ensemble of Low-fidelity Experts: Mitigating NAS "Cold-Start".

Junbo Zhao, Xuefei Ning, Enshu Liu, Binxin Ru, Zixuan Zhou, Tianchen Zhao, Chen Chen, Jiajin Zhang, Qingmin Liao, Yu Wang

CoRR, 2023

Models as Agents: Optimizing Multi-Step Predictions of Interactive Local Models in Model-Based Multi-Agent Reinforcement Learning.

Zifan Wu, Chao Yu, Chen Chen, Jianye Hao, Hankz Hankui Zhuo

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

State-Aware Proximal Pessimistic Algorithms for Offline Reinforcement Learning.

Chen Chen, Hongyao Tang, Yi Ma, Chao Wang, Qianli Shen, Dong Li, Jianye Hao

CoRR, 2022

Rethinking Reinforcement Learning based Logic Synthesis.

Chao Wang, Chen Chen, Dong Li, Bin Wang

CoRR, 2022

Plan To Predict: Learning an Uncertainty-Foreseeing Model For Model-Based Reinforcement Learning.

Zifan Wu, Chao Yu, Chen Chen, Jianye Hao, Hankz Hankui Zhuo

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning Pseudometric-based Action Representations for Offline Reinforcement Learning.

Pengjie Gu, Mengchen Zhao, Chen Chen, Dong Li, Jianye Hao, Bo An

Proceedings of the International Conference on Machine Learning, 2022

What about Inputting Policy in Value Function: Policy Representation and Policy-Extended Value Function Approximator.

Hongyao Tang, Zhaopeng Meng, Jianye Hao, Chen Chen, Daniel Graves, Dong Li, Changmin Yu, Hangyu Mao, Wulong Liu, Yaodong Yang, Wenyuan Tao, Li Wang

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

Creativity of AI: Automatic Symbolic Option Discovery for Facilitating Deep Reinforcement Learning.

Mu Jin, Zhihao Ma, Kebing Jin, Hankz Hankui Zhuo, Chen Chen, Chao Yu

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

2021

Lifelong Reinforcement Learning with Temporal Logic Formulas and Reward Machines.

Xuejing Zheng, Chao Yu, Chen Chen, Jianye Hao, Hankz Hankui Zhuo

CoRR, 2021

CMML: Contextual Modulation Meta Learning for Cold-Start Recommendation.

Xidong Feng, Chen Chen, Dong Li, Mengchen Zhao, Jianye Hao, Jun Wang

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Foresee then Evaluate: Decomposing Value Estimation with Latent Future Prediction.

Hongyao Tang, Zhaopeng Meng, Guangyong Chen, Pengfei Chen, Chen Chen, Yaodong Yang, Luo Zhang, Wulong Liu, Jianye Hao

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Towards Effective Context for Meta-Reinforcement Learning: an Approach based on Contrastive Learning.

Haotian Fu, Hongyao Tang, Jianye Hao, Chen Chen, Xidong Feng, Dong Li, Wulong Liu

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Addressing Action Oscillations through Learning Policy Inertia.

Chen Chen, Hongyao Tang, Jianye Hao, Wulong Liu, Zhaopeng Meng

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

VEGA: Towards an End-to-End Configurable AutoML Pipeline.

Bochao Wang, Hang Xu, Jiajin Zhang, Chen Chen, Yixing Xu, Xiaozhi Fang, Ning Kang, Lanqing Hong, Chenhan Jiang, Xinyue Cai, Jiawei Li, Fengwei Zhou, Yong Li, Zhicheng Liu, Xinghao Chen, Kai Han, Han Shu, Dehua Song, Yunhe Wang, Wei Zhang, Chunjing Xu, Zhenguo Li, Wenzhi Liu, Tong Zhang

CoRR, 2020

What About Taking Policy as Input of Value Function: Policy-extended Value Function Approximator.

Hongyao Tang, Zhaopeng Meng, Jianye Hao, Chen Chen, Daniel Graves, Dong Li, Wulong Liu, Yaodong Yang

CoRR, 2020

MGHRL: Meta Goal-Generation for Hierarchical Reinforcement Learning.

Haotian Fu, Hongyao Tang, Jianye Hao, Wulong Liu, Chen Chen

Proceedings of the Distributed Artificial Intelligence - Second International Conference, 2020

2017

Critical Connectivity and Fastest Convergence Rates of Distributed Consensus With Switching Topologies and Additive Noises.

Ge Chen, Le Yi Wang, Chen Chen, George Yin

IEEE Trans. Autom. Control., 2017

2016

Fast Encoding of Polar Codes With Reed-Solomon Kernel.

Peter Trifonov, Vera Miloslavskaya, Chen Chen, Yuangang Wang

IEEE Trans. Commun., 2016

Performance bounds of distributed adaptive filters with cooperative correlated signals.

Chen Chen, Zhixin Liu, Lei Guo

Sci. China Inf. Sci., 2016

2015

Consensus of flocks under <i>M</i>-nearest-neighbor rules.

Chen Chen, Ge Chen, Lei Guo

J. Syst. Sci. Complex., 2015

Performance analysis of distributed adaptive filters.

Chen Chen, Zhixin Liu, Lei Guo

Commun. Inf. Syst., 2015