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Nan Jiang
Reinforcement Learning
Function Approximation In Reinforcement Learning
Theoretical Foundations Of Reinforcement Learning
About
Hi, this is Nan Jiang (姜楠). I am a machine learning researcher.
I work on building the theoretical foundation of reinforcement learning (RL), especially in the function-approximation setting.
Research Performance Summary
2014-2026
Active Research Span
First Recorded Paper
Improving UCT planning via approximate homomorphisms
Year:
2014
Citations:
57
Venue:
Proceedings of the 2014 international conference on Autonomous agents and
Latest Recorded Paper
Efficient and Robust Behavior Policy Search for Online Off-policy Evaluation through Transition Gradients
Year:
2026
Citations:
0
Venue:
N/A
Last 10 Years Publication Activity
This timeline shows the professor's yearly publication activity.
Publication Venues and Collaboration
Journal, Conference, and Book Publication Breakdown
Top Coauthors
Jiang
Zhang
Huang
Research Impact by Period
Papers
16
Citations
300
Avg. Citations / Paper
18.8
H-Index
7
Papers
49
Citations
3641
Avg. Citations / Paper
74.3
H-Index
28
Papers
30
Citations
5108
Avg. Citations / Paper
170.3
H-Index
21
Papers
1
Citations
57
Avg. Citations / Paper
57
H-Index
1
Contact and Professional Links
Detected Research Keywords
Off Policy Evaluation
Offline Reinforcement Learning
Online Reinforcement Learning
Off Policy Policy
Off Policy Value
Evaluation Reinforcement Learning
Contextual Decision Processes
Batch Reinforcement Learning
Iterative Preference Learning
Learning Human Feedback