Performance analysis of distributed adaptive filters. - Chen Chen 077; Zhixin Liu 003; Lei Guo 001 (Commun. Inf. Syst., 2015)

Consensus of flocks under M-nearest-neighbor rules. - Chen Chen 077; Ge Chen 001; Lei Guo 001 (J. Syst. Sci. Complex., 2015)

Performance bounds of distributed adaptive filters with cooperative correlated signals. - Chen Chen 077; Zhixin Liu 003; Lei Guo 001 (Sci. China Inf. Sci., 2016)

Fast Encoding of Polar Codes With Reed-Solomon Kernel. - Peter Trifonov; Vera Miloslavskaya; Chen Chen 077; Yuangang Wang (IEEE Trans. Commun., 2016)

Critical Connectivity and Fastest Convergence Rates of Distributed Consensus With Switching Topologies and Additive Noises. - Ge Chen 001; Le Yi Wang; Chen Chen 077; George Yin 001 (IEEE Trans. Autom. Control., 2017)

MGHRL: Meta Goal-Generation for Hierarchical Reinforcement Learning. - Haotian Fu; Hongyao Tang; Jianye Hao; Wulong Liu; Chen Chen 077 (DAI, 2020)

What About Taking Policy as Input of Value Function: Policy-extended Value Function Approximator. - Hongyao Tang; Zhaopeng Meng; Jianye Hao; Chen Chen 077; Daniel Graves; Dong Li 016; Wulong Liu; Yaodong Yang 002 (CoRR, 2020)

VEGA: Towards an End-to-End Configurable AutoML Pipeline. - Bochao Wang; Hang Xu 004; Jiajin Zhang; Chen Chen 077; Yixing Xu; Xiaozhi Fang; Ning Kang 001; Lanqing Hong; Chenhan Jiang; Xinyue Cai; Jiawei Li; Fengwei Zhou; et al. (CoRR, 2020)

Addressing Action Oscillations through Learning Policy Inertia. - Chen Chen 077; Hongyao Tang; Jianye Hao; Wulong Liu; Zhaopeng Meng (AAAI, 2021)

Towards Effective Context for Meta-Reinforcement Learning: an Approach based on Contrastive Learning. - Haotian Fu; Hongyao Tang; Jianye Hao; Chen Chen 077; Xidong Feng; Dong Li 016; Wulong Liu (AAAI, 2021)

Foresee then Evaluate: Decomposing Value Estimation with Latent Future Prediction. - Hongyao Tang; Zhaopeng Meng; Guangyong Chen; Pengfei Chen 003; Chen Chen 077; Yaodong Yang 002; Luo Zhang; Wulong Liu; Jianye Hao (AAAI, 2021)

CMML: Contextual Modulation Meta Learning for Cold-Start Recommendation. - Xidong Feng; Chen Chen 077; Dong Li 016; Mengchen Zhao; Jianye Hao; Jun Wang 012 (CIKM, 2021)

Lifelong Reinforcement Learning with Temporal Logic Formulas and Reward Machines. - Xuejing Zheng; Chao Yu 004; Chen Chen 077; Jianye Hao; Hankz Hankui Zhuo (CoRR, 2021)

Creativity of AI: Automatic Symbolic Option Discovery for Facilitating Deep Reinforcement Learning. - Mu Jin; Zhihao Ma; Kebing Jin; Hankz Hankui Zhuo; Chen Chen 077; Chao Yu 004 (AAAI, 2022)

What about Inputting Policy in Value Function: Policy Representation and Policy-Extended Value Function Approximator. - Hongyao Tang; Zhaopeng Meng; Jianye Hao; Chen Chen 077; Daniel Graves; Dong Li 016; Changmin Yu; Hangyu Mao; Wulong Liu; Yaodong Yang 002; Wenyuan Tao; Li Wang (AAAI, 2022)

Learning Pseudometric-based Action Representations for Offline Reinforcement Learning. - Pengjie Gu; Mengchen Zhao; Chen Chen 077; Dong Li 016; Jianye Hao; Bo An 001 (ICML, 2022)

Plan To Predict: Learning an Uncertainty-Foreseeing Model For Model-Based Reinforcement Learning. - Zifan Wu; Chao Yu 004; Chen Chen 077; Jianye Hao; Hankz Hankui Zhuo (NeurIPS, 2022)

Rethinking Reinforcement Learning based Logic Synthesis. - Chao Wang; Chen Chen 077; Dong Li 016; Bin Wang 034 (CoRR, 2022)

State-Aware Proximal Pessimistic Algorithms for Offline Reinforcement Learning. - Chen Chen 077; Hongyao Tang; Yi Ma 005; Chao Wang; Qianli Shen; Dong Li 016; Jianye Hao (CoRR, 2022)

Models as Agents: Optimizing Multi-Step Predictions of Interactive Local Models in Model-Based Multi-Agent Reinforcement Learning. - Zifan Wu; Chao Yu 004; Chen Chen 077; Jianye Hao; Hankz Hankui Zhuo (AAAI, 2023)

Dynamic Ensemble of Low-fidelity Experts: Mitigating NAS "Cold-Start". - Junbo Zhao 001; Xuefei Ning; Enshu Liu; Binxin Ru; Zixuan Zhou; Tianchen Zhao; Chen Chen 077; Jiajin Zhang; Qingmin Liao; Yu Wang 002 (CoRR, 2023)

Hierarchical Task Network Planning for Facilitating Cooperative Multi-Agent Reinforcement Learning. - Xuechen Mu; Hankz Hankui Zhuo; Chen Chen 077; Kai Zhang 012; Chao Yu 004; Jianye Hao (CoRR, 2023)

The Ladder in Chaos: Improving Policy Learning by Harnessing the Parameter Evolving Path in A Low-dimensional Space. - Hongyao Tang; Min Zhang; Chen Chen 077; Jianye Hao (NeurIPS, 2024)

Hierarchical task network-enhanced multi-agent reinforcement learning: Toward efficient cooperative strategies. - Xuechen Mu; Hankz Hankui Zhuo; Chen Chen 077; Kai Zhang 012; Chao Yu 004; Jianye Hao (Neural Networks, 2025)

AttentionPredictor: Temporal Pattern Matters for Efficient LLM Inference. - Qingyue Yang; Jie Wang 005; Xing Li; Zhihai Wang; Chen Chen 077; Lei Chen 031; Xianzhi Yu; Wulong Liu; Jianye Hao; Mingxuan Yuan; Bin Li 025 (CoRR, 2025)