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ORCIDTiancheng Jin
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2020 – today
- 2023
[c13]Tiancheng Jin, Junyan Liu, Haipeng Luo:
Improved Best-of-Both-Worlds Guarantees for Multi-Armed Bandits: FTRL with General Regularizers and Multiple Optimal Arms. NeurIPS 2023- [c12]Tiancheng Jin, Junyan Liu, Chloé Rouyer, William Chang, Chen-Yu Wei, Haipeng Luo:
No-Regret Online Reinforcement Learning with Adversarial Losses and Transitions. NeurIPS 2023 - [c11]Tiancheng Jin, Jianjun Zhao:
ScaffML: A Quantum Behavioral Interface Specification Language for Scaffold. QSW 2023: 128-137 - [c10]Guang Yang, Tiancheng Jin, Liang Dou:
Heterogeneous Directed Hypergraph Neural Network over abstract syntax tree (AST) for Code Classification. SEKE 2023: 274-279 - [i9]Tiancheng Jin, Junyan Liu, Haipeng Luo:
Improved Best-of-Both-Worlds Guarantees for Multi-Armed Bandits: FTRL with General Regularizers and Multiple Optimal Arms. CoRR abs/2302.13534 (2023) - [i8]Guang Yang, Tiancheng Jin, Liang Dou:
Heterogeneous Directed Hypergraph Neural Network over abstract syntax tree (AST) for Code Classification. CoRR abs/2305.04228 (2023) - [i7]Tiancheng Jin, Junyan Liu, Chloé Rouyer, William Chang, Chen-Yu Wei, Haipeng Luo:
No-Regret Online Reinforcement Learning with Adversarial Losses and Transitions. CoRR abs/2305.17380 (2023) - [i6]Tiancheng Jin, Jianjun Zhao:
ScaffML: A Quantum Behavioral Interface Specification Language for Scaffold. CoRR abs/2306.06468 (2023) - 2022
- [j1]Lirong Chen
, Junyi Wang, Hui Wang, Tiancheng Jin:
Urban Air Quality Assessment by Fusing Spatial and Temporal Data from Multiple Study Sources Using Refined Estimation Methods. ISPRS Int. J. Geo Inf. 11(6): 330 (2022) - [c9]Tiancheng Jin, Tal Lancewicki, Haipeng Luo, Yishay Mansour, Aviv Rosenberg:
Near-Optimal Regret for Adversarial MDP with Delayed Bandit Feedback. NeurIPS 2022 - [c8]Yuan Zeng, Tiancheng Jin, Liang Dou:
Difficulty-aware Convolutional Knowledge Tracing for Student Performance Prediction. SmartWorld/UIC/ScalCom/DigitalTwin/PriComp/Meta 2022: 1232-1238 - [i5]Tiancheng Jin, Tal Lancewicki, Haipeng Luo, Yishay Mansour, Aviv Rosenberg:
Near-Optimal Regret for Adversarial MDP with Delayed Bandit Feedback. CoRR abs/2201.13172 (2022) - 2021
- [c7]Xiaoliang Wang, Hexiang Song, Cam-Tu Nguyen, Dongxu Cheng, Tiancheng Jin:
Maximizing the Benefit of RDMA at End Hosts. INFOCOM 2021: 1-10 - [c6]Tiancheng Jin, Longbo Huang, Haipeng Luo:
The best of both worlds: stochastic and adversarial episodic MDPs with unknown transition. NeurIPS 2021: 20491-20502 - [i4]Tiancheng Jin, Longbo Huang, Haipeng Luo:
The best of both worlds: stochastic and adversarial episodic MDPs with unknown transition. CoRR abs/2106.04117 (2021) - 2020
- [c5]Chi Jin, Tiancheng Jin, Haipeng Luo, Suvrit Sra, Tiancheng Yu:
Learning Adversarial Markov Decision Processes with Bandit Feedback and Unknown Transition. ICML 2020: 4860-4869 - [c4]Tiancheng Jin, Haipeng Luo:
Simultaneously Learning Stochastic and Adversarial Episodic MDPs with Known Transition. NeurIPS 2020 - [i3]Tiancheng Jin, Haipeng Luo:
Simultaneously Learning Stochastic and Adversarial Episodic MDPs with Known Transition. CoRR abs/2006.05606 (2020)
2010 – 2019
- 2019
- [c3]John Holler, Risto Vuorio, Zhiwei (Tony) Qin, Xiaocheng Tang, Yan Jiao, Tiancheng Jin, Satinder Singh, Chenxi Wang, Jieping Ye:
Deep Reinforcement Learning for Multi-driver Vehicle Dispatching and Repositioning Problem. ICDM 2019: 1090-1095 - [c2]Tiancheng Jin, Qingshun Wang, Lihua Xu, Chunmei Pan, Liang Dou, Haifeng Qian, Liang He, Tao Xie:
FinExpert: domain-specific test generation for FinTech systems. ESEC/SIGSOFT FSE 2019: 853-862 - [i2]John Holler, Risto Vuorio, Zhiwei (Tony) Qin, Xiaocheng Tang, Yan Jiao, Tiancheng Jin, Satinder Singh, Chenxi Wang, Jieping Ye:
Deep Reinforcement Learning for Multi-Driver Vehicle Dispatching and Repositioning Problem. CoRR abs/1911.11260 (2019) - [i1]Tiancheng Jin, Haipeng Luo:
Learning Adversarial MDPs with Bandit Feedback and Unknown Transition. CoRR abs/1912.01192 (2019) - 2018
- [c1]Feidiao Yang, Tiancheng Jin, Tie-Yan Liu, Xiaoming Sun, Jialin Zhang:
Boosting Dynamic Programming with Neural Networks for Solving NP-hard Problems. ACML 2018: 726-739
Coauthor Index
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