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Computer Science

D-Index
57
Citations
17235
World Ranking
3765
National Ranking
62

Overview

Wee Sun Lee is affiliated with the National University of Singapore in Singapore. Their research primarily lies within the field of Computer Science, with a specific focus on Artificial Intelligence, as well as related subfields such as Computer Vision and Pattern Recognition, Industrial and Manufacturing Engineering, Materials Chemistry, and Management Science and Operations Research.

The scientist's work encompasses multiple topics including Reinforcement Learning in Robotics, Multimodal Machine Learning Applications, Machine Learning and Data Classification, Advanced Graph Neural Networks, Robotic Path Planning Algorithms, Natural Language Processing Techniques, and Domain Adaptation and Few-Shot Learning.

Their publication record features contributions to several venues, notably:

  • arXiv (Cornell University)
  • The International Journal of Robotics Research
  • 2022 International Conference on Robotics and Automation (ICRA)

Some of their recent papers include:

  • "HyP-DESPOT: A hybrid parallel algorithm for online planning under uncertainty" (2020, The International Journal of Robotics Research)
  • "Large Language Models as Commonsense Knowledge for Large-Scale Task Planning" (2023, arXiv (Cornell University))
  • "Learning Latent Graph Dynamics for Visual Manipulation of Deformable Objects" (2022, 2022 International Conference on Robotics and Automation (ICRA))
  • "Discriminative Particle Filter Reinforcement Learning for Complex Partial Observations" (2020, arXiv (Cornell University))
  • "Combining Reinforcement Learning and Optimal Transport for the Traveling Salesman Problem" (2022, arXiv (Cornell University))

Frequent co-authors of Wee Sun Lee include David Hsu, Mohammed Haroon Dupty, Yong Liang Goh, Siddharth Aravindan, and Zichen Liu. Collaboration patterns indicate repeated partnerships, especially with David Hsu and Mohammed Haroon Dupty.

Best Publications

  • Boosting the margin: a new explanation for the effectiveness of voting methods

    Robert E. Schapire;Yoav Freund;Peter Bartlett;Wee Sun Lee

  • SARSOP: Efficient Point-Based POMDP Planning by Approximating Optimally Reachable Belief Spaces

    Hanna Kurniawati;David Hsu;Wee Sun Lee

  • Building text classifiers using positive and unlabeled examples

    B. Liu;Y. Dai;X. Li;W.S. Lee

  • Question classification using support vector machines

    Dell Zhang;Wee Sun Lee

  • Partially Supervised Classification of Text Documents

    Bing Liu;Wee Sun Lee;Philip S. Yu;Xiaoli Li

  • Boosting the margin: A new explanation for the effectiveness of voting methods

    Robert E. Schapire;Yoav Freund;Peter Barlett;Wee Sun Lee

  • An Unsupervised Neural Attention Model for Aspect Extraction.

    Ruidan He;Wee Sun Lee;Hwee Tou Ng;Daniel Dahlmeier

  • Learning with positive and unlabeled examples using weighted logistic regression

    Wee Sun Lee;Bing Liu

  • DESPOT: Online POMDP Planning with Regularization

    Adhiraj Somani;Nan Ye;David Hsu;Wee Sun Lee

  • Convolutional Sequence to Sequence Model for Human Dynamics

    Chen Li;Zhen Zhang;Wee Sun Lee;Gim Hee Lee

  • Intention-aware online POMDP planning for autonomous driving in a crowd

    Haoyu Bai;Shaojun Cai;Nan Ye;David Hsu

  • Planning under Uncertainty for Robotic Tasks with Mixed Observability

    Sylvie C. W. Ong;Shao Wei Png;David Hsu;Wee Sun Lee

  • An Interactive Multi-Task Learning Network for End-to-End Aspect-Based Sentiment Analysis

    Ruidan He;Wee Sun Lee;Hwee Tou Ng;Daniel Dahlmeier

  • Intention-Aware Motion Planning

    Tirthankar Bandyopadhyay;Kok Sung Won;Emilio Frazzoli;David Hsu

  • Exploiting document knowledge for aspect-level sentiment classification

    Ruidan He;Wee Sun Lee;Hwee Tou Ng;Daniel Dahlmeier

  • Text classification by labeling words

    Bing Liu;Xiaoli Li;Wee Sun Lee;Philip S. Yu

  • PORCA: Modeling and Planning for Autonomous Driving Among Many Pedestrians

    Yuanfu Luo;Panpan Cai;Aniket Bera;David Hsu

  • Efficient agnostic learning of neural networks with bounded fan-in

    Wee Sun Lee;P.L. Bartlett;R.C. Williamson

  • Motion planning under uncertainty for robotic tasks with long time horizons

    Hanna Kurniawati;Yanzhu Du;David Hsu;Wee Sun Lee

  • DESPOT: Online POMDP Planning with Regularization

    Nan Ye;Adhiraj Somani;David Hsu;Wee Sun Lee

  • Effective Attention Modeling for Aspect-Level Sentiment Classification

    Ruidan He;Wee Sun Lee;Hwee Tou Ng;Daniel Dahlmeier

Frequent Co-Authors

David Hsu
David Hsu National University of Singapore
Peter L. Bartlett
Peter L. Bartlett University of California, Berkeley
Hwee Tou Ng
Hwee Tou Ng National University of Singapore
Robert C. Williamson
Robert C. Williamson University of Tübingen
Bing Liu
Bing Liu University of Illinois at Chicago
Yee Whye Teh
Yee Whye Teh University of Oxford
Dinesh Manocha
Dinesh Manocha University of Maryland, College Park

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