Yi Ma

Orcid: 0000-0001-9375-6605

Affiliations:

Tianjin University, College of Intelligence and Computing, China

According to our database¹, Yi Ma authored at least 27 papers between 2019 and 2025.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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Bibliography

2025

Squeeze the Soaked Sponge: Efficient Off-policy Reinforcement Finetuning for Large Language Model.

[BibT_eX]

[DOI]

CoRR, July, 2025

2024

Unlock the Intermittent Control Ability of Model Free Reinforcement Learning.

[BibT_eX]

[DOI]

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

CleanDiffuser: An Easy-to-use Modularized Library for Diffusion Models in Decision Making.

[BibT_eX]

[DOI]

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

Iteratively Refined Behavior Regularization for Offline Reinforcement Learning.

[BibT_eX]

[DOI]

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

ENOTO: Improving Offline-to-Online Reinforcement Learning with Q-Ensembles.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Rethinking Decision Transformer via Hierarchical Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Unlock the Cognitive Generalization of Deep Reinforcement Learning via Granular Ball Representation.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Uni-RLHF: Universal Platform and Benchmark Suite for Reinforcement Learning with Diverse Human Feedback.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

A Trajectory Perspective on the Role of Data Sampling Techniques in Offline Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

2023

Prioritized Trajectory Replay: A Replay Memory for Data-driven Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2023

Ensemble-based Offline-to-Online Reinforcement Learning: From Pessimistic Learning to Optimistic Exploration.

[BibT_eX]

[DOI]

CoRR, 2023

HIPODE: Enhancing Offline Reinforcement Learning with High-Quality Synthetic Data from a Policy-Decoupled Approach.

[BibT_eX]

[DOI]

CoRR, 2023

In-Sample Policy Iteration for Offline Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2023

Reining Generalization in Offline Reinforcement Learning via Representation Distinction.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Hierarchical Imitation Learning-based Decision Framework for Autonomous Driving.

[BibT_eX]

[DOI]

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

SplitNet: A Reinforcement Learning Based Sequence Splitting Method for the MinMax Multiple Travelling Salesman Problem.

[BibT_eX]

[DOI]

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

2022

State-Aware Proximal Pessimistic Algorithms for Offline Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2022

PAnDR: Fast Adaptation to New Environments from Offline Experiences via Decoupling Policy and Environment Representations.

[BibT_eX]

[DOI]

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

2021

A Hierarchical Reinforcement Learning Based Optimization Framework for Large-scale Dynamic Pickup and Delivery Problems.

[BibT_eX]

[DOI]

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

A Multi-Graph Attributed Reinforcement Learning based Optimization Algorithm for Large-scale Hybrid Flow Shop Scheduling Problem.

[BibT_eX]

[DOI]

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

2020

Combining sequence and network information to enhance protein-protein interaction prediction.

[BibT_eX]

[DOI]

BMC Bioinform., 2020

KoGuN: Accelerating Deep Reinforcement Learning via Integrating Human Suboptimal Knowledge.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Learning to Accelerate Heuristic Searching for Large-Scale Maximum Weighted b-Matching Problems in Online Advertising.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Dynamic Knapsack Optimization Towards Efficient Multi-Channel Sequential Advertising.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Large Scale Deep Reinforcement Learning in War-games.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020

2019

Spectral-based Graph Convolutional Network for Directed Graphs.

[BibT_eX]

[DOI]

CoRR, 2019

Integrating Sequence and Network Information to Enhance Protein-Protein Interaction Prediction Using Graph Convolutional Networks.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

Yi Ma

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