Boosting Dynamic Programming with Neural Networks for Solving NP-hard Problems. - Feidiao Yang; Tiancheng Jin; Tie-Yan Liu; Xiaoming Sun 001; Jialin Zhang 001 (ACML, 2018)

Deep Reinforcement Learning for Multi-driver Vehicle Dispatching and Repositioning Problem. - John Holler; Risto Vuorio; Zhiwei (Tony) Qin; Xiaocheng Tang; Yan Jiao; Tiancheng Jin; Satinder Singh 001; Chenxi Wang; Jieping Ye (ICDM, 2019)

FinExpert: domain-specific test generation for FinTech systems. - Tiancheng Jin; Qingshun Wang; Lihua Xu; Chunmei Pan; Liang Dou; Haifeng Qian; Liang He 001; Tao Xie 001 (ESEC/SIGSOFT FSE, 2019)

Learning Adversarial MDPs with Bandit Feedback and Unknown Transition. - Tiancheng Jin; Haipeng Luo (CoRR, 2019)

Learning Adversarial Markov Decision Processes with Bandit Feedback and Unknown Transition. - Chi Jin 001; Tiancheng Jin; Haipeng Luo; Suvrit Sra; Tiancheng Yu (ICML, 2020)

Simultaneously Learning Stochastic and Adversarial Episodic MDPs with Known Transition. - Tiancheng Jin; Haipeng Luo (NeurIPS, 2020)

Maximizing the Benefit of RDMA at End Hosts. - Xiaoliang Wang 001; Hexiang Song; Cam-Tu Nguyen; Dongxu Cheng; Tiancheng Jin (INFOCOM, 2021)

The best of both worlds: stochastic and adversarial episodic MDPs with unknown transition. - Tiancheng Jin; Longbo Huang; Haipeng Luo (NeurIPS, 2021)

Near-Optimal Regret for Adversarial MDP with Delayed Bandit Feedback. - Tiancheng Jin; Tal Lancewicki; Haipeng Luo; Yishay Mansour; Aviv Rosenberg 002 (NeurIPS, 2022)

Difficulty-aware Convolutional Knowledge Tracing for Student Performance Prediction. - Yuan Zeng; Tiancheng Jin; Liang Dou (SmartWorld/UIC/ScalCom/DigitalTwin/PriComp/Meta, 2022)

Urban Air Quality Assessment by Fusing Spatial and Temporal Data from Multiple Study Sources Using Refined Estimation Methods. - Lirong Chen; Junyi Wang; Hui Wang; Tiancheng Jin (ISPRS Int. J. Geo Inf., 2022)

Improved Best-of-Both-Worlds Guarantees for Multi-Armed Bandits: FTRL with General Regularizers and Multiple Optimal Arms. - Tiancheng Jin; Junyan Liu; Haipeng Luo (NeurIPS, 2023)

No-Regret Online Reinforcement Learning with Adversarial Losses and Transitions. - Tiancheng Jin; Junyan Liu; Chloé Rouyer; William Chang; Chen-Yu Wei; Haipeng Luo (NeurIPS, 2023)

ScaffML: A Quantum Behavioral Interface Specification Language for Scaffold. - Tiancheng Jin; Jianjun Zhao 001 (QSW, 2023)

Heterogeneous Directed Hypergraph Neural Network over abstract syntax tree (AST) for Code Classification. - Guang Yang; Tiancheng Jin; Liang Dou (SEKE, 2023)

GMP-TL: Gender-Augmented Multi-Scale Pseudo-Label Enhanced Transfer Learning For Speech Emotion Recognition. - Yu Pan 008; Yuguang Yang 005; Yuheng Huang 004; Tiancheng Jin; Jingjing Yin; Yanni Hu; Heng Lu 004; Lei Ma 003; Jianjun Zhao 001 (SLT, 2024)