Wang Kaixin
I am a postdoctoral researcher in
Prof. Shie Mannor 's group at Technion.
Previously, I finished my PhD study in
Institute of Data Science
at National University of Singapore,
fortunately supervised by
Prof. Bryan Hooi ,
Dr. Jiashi Feng and
Prof. Xinchao Wang .
Even earlier, I spent my undergraduate years at Nanjing University.
I am broadly interested in topics in (deep) reinforcement learning,
such as state/action representation, exploration and generalization.
I particularly enjoy doing research that answers an interesting question
or resolves an open issue. Feel free to contact me for discussion
or collaboration!
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CV
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Selected
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All
Research Works
Jointly Modelling Uncertainty and Diversity for Active Molecular Property Prediction
Kuangqi Zhou, Kaixin Wang , Jian Tang, Jiashi Feng, Bryan Hooi, Peilin Zhao, Tingyang Xu, Xinchao Wang
LoG , 2022
Reachability-Aware Laplacian Representation in Reinforcement Learning
Kaixin Wang , Kuangqi Zhou, Jiashi Feng, Bryan Hooi, Xinchao Wang
arXiv , 2022
arXiv
Relational Reasoning via Set Transformers: Provable Efficiency and Applications to MARL
Fengzhuo Zhang, Boyi Liu, Kaixin Wang , Vincent Y. F. Tan, Zhuoran Yang, Zhaoran Wang
NeurIPS , 2022
arXiv
Efficient Policy Iteration for Robust Markov Decision Processes via Regularization
Navdeep Kumar, Kfir Levy, Kaixin Wang , Shie Mannor
arXiv , 2022
arXiv
Tyger: Task-Type-Generic Active Learning for Molecular Property Prediction
Kuangqi Zhou, Kaixin Wang , Jiashi Feng, Jian Tang, Tingyang Xu, Xinchao Wang
arXiv , 2022
arXiv
Policy Gradient for Reinforcement Learning with General Utilities
Navdeep Kumar, Kaixin Wang , Kfir Levy, Shie Mannor
RLDM , 2022
The Geometry of Robust Value Functions
Kaixin Wang , Navdeep Kumar, Kuangqi Zhou, Bryan Hooi, Jiashi Feng,
Shie Mannor
ICML , 2022
arXiv
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presentation
Understanding and Resolving Performance Degradation in Graph
Convolutional Networks
Kuangqi Zhou*, Yanfei Dong*, Kaixin Wang , Wee Sun Lee, Bryan Hooi,
Huan Xu, Jiashi Feng
CIKM , 2021
arXiv
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code
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presentation
Towards Better Laplacian Representation in Reinforcement Learning
with
Generalized Graph Drawing
Kaixin Wang* , Kuangqi Zhou*, Qixin Zhang, Jie Shao, Bryan Hooi,
Jiashi Feng
ICML , 2021
arXiv
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code (coming soon)
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presentation
Improving Generalization in Reinforcement Learning with Mixture
Regularization
Kaixin Wang , Bingyi Kang, Jie Shao, Jiashi Feng
NeurIPS , 2020
arXiv
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code
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site
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presentation
Neural Epitome Search for Architecture-Agnostic Network Compression
Daquan Zhou, Xiaojie Jin, Qibin Hou, Kaixin Wang , Jianchao Yang,
Jiashi Feng
ICLR , 2020
arXiv
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code
 / 
presentation
PANet: Few-Shot Image Semantic Segmentation with Prototype Alignment
Kaixin Wang , Jun Hao Liew, Yingtian Zou, Daquan Zhou, Jiashi Feng
ICCV , 2019
arXiv
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code
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presentation
Academic Services
Volunteer
Reviewer
Top reviewer
AAAI:
2023
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ICLR:
2020
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,
2021
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,
2022
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,
2023
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ICML:
2020
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,
2021
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)
,
2022
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NeurIPS:
2020
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,
2021
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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Transactions on Machine Learning Research
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IEEE Transactions on Image Processing
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IEEE Transactions on Multimedia
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Machine Vision and Applications
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My Academic Toolbox
🎨 Draw.io (now diagrams.net) :
A very powerful yet easy-to-use tool for creating diagrams / plots.
💿 PaperMemory :
A handy browser extension to store papers I read, and much more.
📐 GeoGebra :
A nice tool for interactive visualization of 2D/3D geometry.
∭ LaTeXiT :
A handy equation editor when I do need LaTex rather than MathJax (e.g. , using euscript
font).
This page is forked from here 🚀