default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDChenjun Xiao
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
[c21]Xiaotian Hao, Jianye Hao, Chenjun Xiao, Kai Li, Dong Li, Yan Zheng:
Multiagent Gumbel MuZero: Efficient Planning in Combinatorial Action Spaces. AAAI 2024: 12304-12312- [c20]Fengdi Che, Chenjun Xiao, Jincheng Mei, Bo Dai, Ramki Gummadi, Oscar A. Ramirez, Christopher K. Harris, A. Rupam Mahmood, Dale Schuurmans:
Target Networks and Over-parameterization Stabilize Off-policy Bootstrapping with Function Approximation. ICML 2024 - [c19]Haoyu Ma, Jialong Wu, Ningya Feng, Chenjun Xiao, Dong Li, Jianye Hao, Jianmin Wang, Mingsheng Long:
HarmonyDream: Task Harmonization Inside World Models. ICML 2024 - [c18]Yi Ma, Jianye Hao, Hebin Liang, Chenjun Xiao:
Rethinking Decision Transformer via Hierarchical Reinforcement Learning. ICML 2024 - [c17]Hongming Zhang, Tongzheng Ren, Chenjun Xiao, Dale Schuurmans, Bo Dai:
Provable Representation with Efficient Planning for Partially Observable Reinforcement Learning. ICML 2024 - [i15]Yangchen Pan, Junfeng Wen, Chenjun Xiao, Philip Torr:
An MRP Formulation for Supervised Learning: Generalized Temporal Difference Learning Models. CoRR abs/2404.15518 (2024) - [i14]Fengdi Che, Chenjun Xiao, Jincheng Mei, Bo Dai, Ramki Gummadi, Oscar A. Ramirez, Christopher K. Harris, A. Rupam Mahmood, Dale Schuurmans:
Target Networks and Over-parameterization Stabilize Off-policy Bootstrapping with Function Approximation. CoRR abs/2405.21043 (2024) - [i13]Dmitry Shribak, Chen-Xiao Gao, Yitong Li, Chenjun Xiao, Bo Dai:
Diffusion Spectral Representation for Reinforcement Learning. CoRR abs/2406.16121 (2024) - [i12]Chen-Xiao Gao, Shengjun Fang, Chenjun Xiao, Yang Yu, Zongzhang Zhang:
Hindsight Preference Learning for Offline Preference-based Reinforcement Learning. CoRR abs/2407.04451 (2024) - 2023
- [c16]Tongzheng Ren, Chenjun Xiao, Tianjun Zhang, Na Li, Zhaoran Wang, Sujay Sanghavi, Dale Schuurmans, Bo Dai:
Latent Variable Representation for Reinforcement Learning. ICLR 2023 - [c15]Chenjun Xiao, Han Wang, Yangchen Pan, Adam White, Martha White:
The In-Sample Softmax for Offline Reinforcement Learning. ICLR 2023 - [c14]Hongming Zhang, Chenjun Xiao, Han Wang, Jun Jin, Bo Xu, Martin Müller:
Replay Memory as An Empirical MDP: Combining Conservative Estimation with Experience Replay. ICLR 2023 - [c13]Tianjun Zhang, Tongzheng Ren, Chenjun Xiao, Wenli Xiao, Joseph E. Gonzalez, Dale Schuurmans, Bo Dai:
Energy-based Predictive Representations for Partially Observed Reinforcement Learning. UAI 2023: 2477-2487 - [c12]Xutong Zhao, Yangchen Pan
, Chenjun Xiao, Sarath Chandar, Janarthanan Rajendran:
Conditionally optimistic exploration for cooperative deep multi-agent reinforcement learning. UAI 2023: 2529-2540 - [i11]Chenjun Xiao, Han Wang, Yangchen Pan, Adam White, Martha White:
The In-Sample Softmax for Offline Reinforcement Learning. CoRR abs/2302.14372 (2023) - [i10]Xutong Zhao, Yangchen Pan, Chenjun Xiao, Sarath Chandar, Janarthanan Rajendran:
Conditionally Optimistic Exploration for Cooperative Deep Multi-Agent Reinforcement Learning. CoRR abs/2303.09032 (2023) - [i9]Xiaohan Hu, Yi Ma, Chenjun Xiao, Yan Zheng, Zhaopeng Meng:
In-Sample Policy Iteration for Offline Reinforcement Learning. CoRR abs/2306.05726 (2023) - [i8]Yi Ma, Chenjun Xiao, Hebin Liang, Jianye Hao:
Rethinking Decision Transformer via Hierarchical Reinforcement Learning. CoRR abs/2311.00267 (2023) - [i7]Hongming Zhang, Tongzheng Ren, Chenjun Xiao, Dale Schuurmans, Bo Dai:
Provable Representation with Efficient Planning for Partially Observable Reinforcement Learning. CoRR abs/2311.12244 (2023) - 2022
- [c11]Chenjun Xiao, Ilbin Lee, Bo Dai, Dale Schuurmans, Csaba Szepesvári:
The Curse of Passive Data Collection in Batch Reinforcement Learning. AISTATS 2022: 8413-8438 - [c10]Chenjun Xiao, Bo Dai, Jincheng Mei, Oscar A. Ramirez, Ramki Gummadi, Chris Harris, Dale Schuurmans:
Understanding and Leveraging Overparameterization in Recursive Value Estimation. ICLR 2022 - [i6]Tongzheng Ren, Chenjun Xiao, Tianjun Zhang, Na Li, Zhaoran Wang, Sujay Sanghavi, Dale Schuurmans, Bo Dai:
Latent Variable Representation for Reinforcement Learning. CoRR abs/2212.08765 (2022) - 2021
- [c9]Chenjun Xiao, Yifan Wu, Jincheng Mei, Bo Dai, Tor Lattimore, Lihong Li, Csaba Szepesvári, Dale Schuurmans:
On the Optimality of Batch Policy Optimization Algorithms. ICML 2021: 11362-11371 - [c8]Jincheng Mei, Bo Dai, Chenjun Xiao, Csaba Szepesvári, Dale Schuurmans:
Understanding the Effect of Stochasticity in Policy Optimization. NeurIPS 2021: 19339-19351 - [i5]Chenjun Xiao, Yifan Wu, Tor Lattimore, Bo Dai, Jincheng Mei, Lihong Li, Csaba Szepesvári, Dale Schuurmans:
On the Optimality of Batch Policy Optimization Algorithms. CoRR abs/2104.02293 (2021) - [i4]Chenjun Xiao, Ilbin Lee, Bo Dai, Dale Schuurmans, Csaba Szepesvári:
On the Sample Complexity of Batch Reinforcement Learning with Policy-Induced Data. CoRR abs/2106.09973 (2021) - [i3]Jincheng Mei, Bo Dai, Chenjun Xiao, Csaba Szepesvári, Dale Schuurmans:
Understanding the Effect of Stochasticity in Policy Optimization. CoRR abs/2110.15572 (2021) - 2020
- [c7]Jincheng Mei, Chenjun Xiao, Csaba Szepesvári, Dale Schuurmans:
On the Global Convergence Rates of Softmax Policy Gradient Methods. ICML 2020: 6820-6829 - [c6]Jincheng Mei, Chenjun Xiao, Bo Dai, Lihong Li, Csaba Szepesvári, Dale Schuurmans:
Escaping the Gravitational Pull of Softmax. NeurIPS 2020 - [i2]Jincheng Mei, Chenjun Xiao, Csaba Szepesvári, Dale Schuurmans:
On the Global Convergence Rates of Softmax Policy Gradient Methods. CoRR abs/2005.06392 (2020)
2010 – 2019
- 2019
- [c5]Jincheng Mei, Chenjun Xiao, Ruitong Huang, Dale Schuurmans, Martin Müller:
On Principled Entropy Exploration in Policy Optimization. IJCAI 2019: 3130-3136 - [c4]Chenjun Xiao, Ruitong Huang, Jincheng Mei, Dale Schuurmans, Martin Müller:
Maximum Entropy Monte-Carlo Planning. NeurIPS 2019: 9516-9524 - [i1]Chenjun Xiao, Yifan Wu, Chen Ma, Dale Schuurmans, Martin Müller:
Learning to Combat Compounding-Error in Model-Based Reinforcement Learning. CoRR abs/1912.11206 (2019) - 2018
- [c3]Chenjun Xiao, Jincheng Mei, Martin Müller:
Memory-Augmented Monte Carlo Tree Search. AAAI 2018: 1455-1462 - 2017
- [j2]Jiao Wang, Chenjun Xiao, Tan Zhu, Chu-Hsuan Hsueh, Wen-Jie Tseng, I-Chen Wu:
Only-One-Victor Pattern Learning in Computer Go. IEEE Trans. Comput. Intell. AI Games 9(1): 88-102 (2017) - 2016
- [c2]Chenjun Xiao, Martin Müller:
Factorization Ranking Model for Move Prediction in the Game of Go. AAAI 2016: 1359-1365 - [c1]Chenjun Xiao, Martin Müller:
Integrating Factorization Ranked Features in MCTS: An Experimental Study. CGW@IJCAI 2016: 34-43 - 2012
- [j1]Jiao Wang, Hongye Li, Chenjun Xiao, Xin-He Xu:
The 2nd National University Student Computer-Games Tournaments. J. Int. Comput. Games Assoc. 35(3): 182-185 (2012)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-11-13 23:52 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
