1. Kwang-Sung Jun, Aniruddha Bhargava, Robert Nowak, and Rebecca Willett. “Scalable Generalized Linear Bandits: Online Computation and Hashing”. Arxiv preprint, 2017. [arxiv]

  2. Kwang-Sung Jun, Francesco Orabona, Rebecca Willett, and Stephen Wright. “Improved Strongly Adaptive Online Learning using Coin Betting”. In AISTATS, 2017. Oral presentation. [official] [arxiv]

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

  4. Jeffrey Zemla, Yoed Kenett, Kwang-Sung Jun, and Joseph Austerweil. “U-INVITE: Estimating Individual Semantic Networks from Fluency Data”. In Proceedings of the 38th Annual Meeting of the Cognitive Science Society, 2016. [pdf]

  5. Kwang-Sung Jun and Robert Nowak. “Anytime Exploration for Multi-armed Bandits using Confidence Information”. In ICML, 2016. [pdf]

  6. Kwang-Sung Jun, Kevin Jamieson, Rob Nowak, and Xiaojin Zhu. “Top arm identification in multi-armed bandits with batch arm pulls”. In AISTATS, 2016. [pdf]

  7. Kwang-Sung Jun, Xiaojin Zhu, Timothy Rogers, Zhuoran Yang, and Ming Yuan. “Human memory search as initial-visit emitting random walk”. In NIPS, 2015. [pdf]

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

  9. Kwang-Sung Jun, Xiaojin Zhu, Burr Settles, and Timothy Rogers. “Learning from Human-Generated Lists”. In ICML, 2013. [pdf] [code&data] [video]

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

  11. Jun-Ming Xu, Kwang-Sung Jun, Xiaojin Zhu, and Amy Bellmore. “Learning from bullying traces in social media”. In NAACL HLT, 2012. [pdf]

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

  13. Xiaojin Zhu, Bryan R. Gibson, Kwang-Sung Jun, Timothy T. Rogers, Joseph Harrison, and Chuck Kalish. “Cognitive models of test-item effects in human category learning”. In ICML, 2010. [pdf]

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