1. Scalable Generalized Linear Bandits: Online Computation and Hashing.
    Kwang-Sung Jun, Aniruddha Bhargava, Robert Nowak, and Rebecca Willett.
    In Neural Information Processing Systems (NIPS), 2017. [arxiv]

  2. Identifying Multiple Authors in a Binary Program.
    Xiaozhu Meng, Barton P. Miller, and Kwang-Sung Jun.
    In European Symposium on Research in Computer Security (ESORICS), 2017.

  3. Improved Strongly Adaptive Online Learning using Coin Betting.
    Kwang-Sung Jun, Francesco Orabona, Rebecca Willett, and Stephen Wright.
    In International Conference on Artificial Intelligence and Statistics (AISTATS), 2017. Oral presentation. [official] [arxiv]

  4. Graph-Based Active Learning: A New Look at Expected Error Minimization.
    Kwang-Sung Jun and Robert Nowak.
    In IEEE GlobalSIP Symposium on Non-Commutative Theory and Applications, 2016. [ieee][arxiv]

  5. U-INVITE: Estimating Individual Semantic Networks from Fluency Data.
    Jeffrey Zemla, Yoed Kenett, Kwang-Sung Jun, and Joseph Austerweil.
    In Proceedings of the Annual Meeting of the Cognitive Science Society, 2016. [pdf]

  6. Anytime Exploration for Multi-armed Bandits using Confidence Information.
    Kwang-Sung Jun and Robert Nowak.
    In International Conference on Machine Learning (ICML), 2016. [pdf]

  7. Top arm identification in multi-armed bandits with batch arm pulls.
    Kwang-Sung Jun, Kevin Jamieson, Rob Nowak, and Xiaojin Zhu.
    In International Conference on Artificial Intelligence and Statistics (AISTATS), 2016. [pdf]

  8. Human memory search as initial-visit emitting random walk.
    Kwang-Sung Jun, Xiaojin Zhu, Timothy Rogers, Zhuoran Yang, and Ming Yuan.
    In Neural Information Processing Systems (NIPS), 2015. [pdf]

  9. Smarter Crisis Crowdsourcing.
    Kayla Jacobs, Kwang-Sung Jun, Nathan Lieby, and Elena Eneva.
    In ACM SIGKDD Workshop on Data Science for Social Good, 2014. [pdf]

  10. Learning from Human-Generated Lists.
    Kwang-Sung Jun, Xiaojin Zhu, Burr Settles, and Timothy Rogers.
    In International Conference on Machine Learning (ICML), 2013. [pdf] [code&data] [video]

  11. An Image-To-Speech iPad App.
    Michael Maynord, Jitrapon Tiachunpun, Xiaojin Zhu, Charles R. Dyer, Kwang-Sung Jun, and Jake Rosin.
    Department of Computer Sciences Technical Report TR1774, University of Wisconsin-Madison, 2012.

  12. Learning from bullying traces in social media.
    Jun-Ming Xu, Kwang-Sung Jun, Xiaojin Zhu, and Amy Bellmore.
    In the Conference of North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL HLT), 2012. [pdf]

  13. With a little help from the computer: Hybrid human-machine systems on bandit problems.
    Bryan Gibson, Kwang-Sung Jun, and Xiaojin Zhu.
    In NIPS Workshop on Computational Social Science and the Wisdom of Crowds, 2010. [pdf]

  14. Cognitive models of test-item effects in human category learning.
    Xiaojin Zhu, Bryan R. Gibson, Kwang-Sung Jun, Timothy T. Rogers, Joseph Harrison, and Chuck Kalish.
    In International Conference on Machine Learning (ICML), 2010. [pdf]

  15. An efficient collaborative filtering method based on k-nearest neighbor learning for large-scale data.
    Kwang-Sung Jun and Kyu-Baek Hwang.
    In Proceedings of Korea Computer Congress, 2008.