Publications

Complete list in reverse chronological order



1. Jungtaek Kim, Minsu Cho, and Seungjin Choi (2022),
   "Combinatorial Bayesian optimization with random mapping functions to convex polytope,"
   Proceedings of the 38th Conference on Uncertainty in Artificial Intelligence (UAI-2022),
   Eindhoven, Netherlands, August 1-5, 2022.
   (earlier version in preprint arXiv:2011.13094 )
   

2. Jungtaek Kim and Seungjin Choi (2022),
   "On uncertainty estimation by tree-based surrogate models in sequential model-based optimization,"
   Proceedings of The 25th International Conference on Artificial Intelligence and Statistics (AISTATS-2022),
   virtual-only conference, March 28-30, 2022.
   (earlier version in preprint arXiv:2202.10669 )
   

3. Jungtaek Kim, Michael McCourt, Tackgeun You, Saehoon Kim, and Seungjin Choi (2021),
   "Bayesian optimization with approximate set kernels,"
   Machine Learning
   vol. 110, issue 5, pp. 857-879, May 2021.
   (earlier version in preprint arXiv:1905.09780 )
   

4. Yoonho Lee, Juho Lee, Sung Ju Hwang, Eunho Yang, and Seungjin Choi (2020),
   "Neural complexity measures,"
   Advances in Neural Information Processing Systems 33 (NeurIPS-2020),
   Virtual-only conference, December 6-12, 2020.
   (earlier version in preprint arXiv:2008.02953 )
   

5. Jungtaek Kim and Seungjin Choi (2020),
   "On local optimizers of acquisition functions in Bayesian optimization,"
   Proceedings of the European Conference on Machine Learning and
   Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD-2020),
   Virtual-only conference, September 14-18, 2020.
   (earlier version in preprint arXiv:1901.08350 )
   

6. Juho Lee, Yoonho Lee, Jungtaek Kim, Adam R. Kosiorek, Seungjin Choi, Yee Whye Teh (2019),
   "Set transformer: A framework for attention-based permutation-invariant neural networks,"
   Proceedings of the Thirty-Sixth International Conference on Machine Learning (ICML-2019),
   Long Beach, California, USA, June 9-15, 2019.
   (earlier version in preprint arXiv:1810.00825 )
   

7. Juho Lee, Lancelot James, Seungjin Choi, and François Caron (2019),
   "A Bayesian model for sparse graphs with flexible degree distribution and overlapping community structure,"
   Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS-2019),
   Naha, Okinawa, Japan, April 16-18, 2019. (oral)
   (earlier version in preprint arXiv:1810.01778 )
   

8. Yoonho Lee and Seungjin Choi (2018),
   "Gradient-based meta-learning with adaptive layerwise metric and subspace,"
   in Proceedings of the Thirty-Fifth International Conference on Machine Learning (ICML-2018),
   Stockholm, Sweden, July 10-15, 2018.
   (earlier version in preprint arXiv:1810.05558 )
   

9. Saehoon Kim, Jungtaek Kim, and Seungjin Choi (2018),
   "On the optimal bit complexity of circulant binary embedding,"
   in Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-2018),
   New Orleans, Louisiana, USA, February 2-7, 2018.
   

10. Juho Lee, Creighton Heaukulani, Zoubin Ghahramani, Lancelot James, and Seungjin Choi (2017),
    "Bayesian inference on random simple graphs with power law degree distributions,"
    in Proceedings of the International Conference on Machine Learning (ICML-2017),
    Sydney, Australia, August 6-11, 2017.
    (earlier version in preprint arXiv:1702.08239 )
    

11. Saehoon Kim and Seungjin Choi (2017),
    "Binary embedding with additive homogeneous kernels,"
    in Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-2017),
    San Francisco, California, USA, February 4-9, 2017.
    

12. Juho Lee, Lancelot F. James, and Seungjin Choi (2016),
    "Finite-dimensional BFRY priors and variational Bayesian inference for power law models,"
    in Advances in Neural Information Processing Systems 29 (NIPS-2016),
    Barcelona, Spain, December 5-10, 2016.
    

13. Suwon Suh and Seungjin Choi (2016),
    "Gaussian copula variational autoencoders for mixed data,"
    Preprint arXiv:1604.04960, 2016.
    

14. Yong-Deok Kim, Taewoong Jang, Bohyung Han, and Seungjin Choi (2016),
    "Learning to select pre-trained deep representations with Bayesian evidence framework,"
    in Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition (CVPR-2016),
    Las Vegas, Nevada, USA, June 27-30, 2016. (oral)
    

15. Juho Lee and Seungjin Choi (2015),
    "Tree-guided MCMC inference for normalized random measure mixture models,"
    in Advances in Neural Information Processing Systems 28 (NIPS-2015),
    Montreal, Canada, December 7-12, 2015.
    

16. Saehoon Kim and Seungjin Choi (2015),
    "Bilinear random projections for locality-sensitive binary embedding,"
    in Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition (CVPR-2015),
    Boston, Massachusetts, USA, June 7-12, 2015.
    

17. Juho Lee and Seungjin Choi (2015),
    "Bayesian hierarchical clustering with exponential family: Small-variance asymptotics and reducibility,"
    in Proceedings of the 18th International Conference on Artificial Intelligence and Statistics (AISTATS-2015),
    San Diego, California, USA, May 9-12, 2015.
    

18. Saehoon Kim, Yuxiong He, Seung-won Hwang, Sameh Elnikety, and Seungjin Choi (2015),
    "Delayed-dynamic-selective (DDS) prediction for reducing extreme tail latency in web search,"
    in Proceedings of the 8th ACM International Conference on Web Search and Data Mining (WSDM-2015),
    Shanghai, China, February 2-6, 2015.
    (Best paper runnerup)
    

19. Yong-Deok Kim and Seungjin Choi (2014),
    "Bayesian binomial mixture model for collaborative prediction with non-random missing data,"
    in Proceedings of the 8th ACM Conference on Recommender Systems (RecSys-2014),
    Foster City, Silicon Valley, USA, October 6-10, 2014.
    

20. Yongsoo Kim, Jin-Hyeok Jang, Seungjin Choi, and Daehee Hwang (2014),
    "TEMPI: Probabilistic modeling Time-Evolving differential PPI networks with MultiPle Information,"
    in Proceedings of the Thirteenth European Conference on Computational Biology (ECCB-2014),
    Strasbourg, France, September 7-10, 2014.
    

21. Juho Lee and Seungjin Choi (2014),
    "Incremental tree-based inference with dependent normalized random measures,"
    in Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics (AISTATS-2014),
    Reykjavik, Iceland, April 22-25, 2014.
    

22. Yong-Deok Kim and Seungjin Choi (2014),
    "Scalable variational Bayesian matrix factorization with side information,"
    in Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics (AISTATS-2014),
    Reykjavik, Iceland, April 22-25, 2014.
    

23. Sunho Park, Tae Hyun Hwang, and Seungjin Choi (2014),
    "Convex optimization for binary classifier aggregation in multiclass problems,"
    in Proceedings of the SIAM International Conference on Data Mining (SDM-2014),
    Philadelphia, Pennsylvania, USA, April 24-26, 2014.
    

24. Sunho Park, Yong-Deok Kim, and Seungjin Choi (2013),
    "Hierarchical Bayesian matrix factorization with side information,"
    in Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence (IJCAI-2013),
    Beijing, China, August 3-9, 2013.
    

25. Kye-Hyeon Kim and Seungjin Choi (2013),
    "Walking on minimax paths for k-NN search,"
    in Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence (AAAI-2013),
    Bellevue, Washington, USA, July 16-18, 2013.
    

26. Jeong-Min Yun, Saehoon Kim, and Seungjin Choi (2012),
    "Hashing with generalized Nystrom approximation,"
    in Proceedings of the IEEE International Conference on Data Mining (ICDM-2012),
    Brussels, Belgium, December 10-13, 2012.
    

27. Yoonseop Kang, Saehoon Kim, and Seungjin Choi (2012),
    "Deep learning to hash with multiple representations,"
    in Proceedings of the IEEE International Conference on Data Mining (ICDM-2012),
    Brussels, Belgium, December 10-13, 2012.
    

28. Saehoon Kim, Yoonseop Kang and Seungjin Choi (2012),
    "Sequential spectral learning to hash with multiple representations,"
    in Proceedings of the 12th European Conference on Computer Vision (ECCV-2012),
    Firenze, Italy, October 7-13, 2012.
    

29. Juho Lee, Suha Kwak, Bohyung Han, and Seungjin Choi (2012),
    "Online video segmentation by Bayesian split-merge clustering,"
    in Proceedings of the 12th European Conference on Computer Vision (ECCV-2012),
    Firenze, Italy, October 7-13, 2012.
    

30. Hyohyeong Kang and Seungjin Choi (2012),
    "Probabilistic models for common spatial patterns: Parameter-expanded EM and variational Bayes,"
    in Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI-2012),
    Toronto, Canada, July 22-26, 2012.
    

31. Saehoon Kim and Seungjin Choi (2011),
    "Semi-supervised discriminant hashing,"
    in Proceedings of the Eleventh IEEE International Conference on Data Mining (ICDM-2011),
    Vancouver, Canada, December 11-14, 2011.
    

32. Yoonseop Kang and Seungjin Choi (2011),
    "Restricted deep belief networks for multi-view learning,"
    in Proceedings of the European Conference on Machine Learning
    and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD-2011),
    Athens, Greece, September 5-9, 2011.

33. Jiho Yoo and Seungjin Choi (2011),
    "Bayesian matrix co-factorization: Variational algorithm and Cramer-Rao bound,"
    in Proceedings of the European Conference on Machine Learning
    and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD-2011),
    Athens, Greece, September 5-9, 2011.

34. Jiho Yoo and Seungjin Choi (2011),
    "Matrix co-factorization on compressed sensing,"
    in Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence (IJCAI-2011),
    Barcelona, Spain, July 16-22, 2011.
    

35. Sunho Park and Seungjin Choi (2010),
    "Bayesian aggregation of binary classifiers,"
    in Proceedings of the Tenth IEEE International Conference on Data Mining (ICDM-2010),
    Sydney, Australia, December 14-17, 2010.
    

36. Jong Kyoung Kim and Seungjin Choi (2009),
    "Clustering sequence sets for motif discovery,"
    in Advances in Neural Information Processing Systems 22 (NIPS-2009),
    edited by Y. Bengio, D. Schuurmans, J. Lafferty, C. K. I. Williams and A. Culotta,
    Vancouver, Canada, December 7-10, 2009.
    

37. Hyekyoung Lee and Seungjin Choi (2009),
    "Group nonnegative matrix factorization for EEG classification,"
    in Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS-2009),
    Clearwater Beach, Florida, April 16-18, 2009.
    

38. Andrzej Cichocki, Yoshikazu Washizawa, Tomasz Rutkowski, Hovagim Bakardjian, Anh-Huy Phan,
    Seungjin Choi, Hyekyoung Lee, Qibin Zhao, Liqing Zhang, and Yuanqing Li (2008),
    "Noninvasive BCIs: Multiway signal-processing array decompositions"
    IEEE Computer,
    vol. 41, no. 10, pp. 34-42, October 2008.
    

39. Heeyoul Choi, Seungjin Choi, and Yoonsuck Choe (2008),
    "Manifold integration with Markov random walks,"
    in Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence (AAAI-2008),
    Chicago, Illinois, July 13-17, 2008.
    

40. Kye-Hyeon Kim and Seungjin Choi (2007)
    "Neighbor search with global geometry: A minimax message passing algorithm,"
    in Proceedings of the International Conference on Machine Learning (ICML-2007),
    Corvallis, Oregon, June 20-24, 2007.

41. Yong-Deok Kim and Seungjin Choi (2007),
    "Nonnegative Tucker decomposition,"
    in Proceedings of the IEEE CVPR-2007 Workshop on Component Analysis Methods,
    Minneapolis, Minnesota, June 22, 2007.
    

42. Seunghak Lee, Iryoung Jeong, and Seungjin Choi (2007),
    "Dynamically weighted hidden Markov model for spam deobfuscation,"
    in Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI-2007),
    Hyderabad, India, January 6-12, 2007.
    

43. Jong-Hoon Ahn, Seungjin Choi, and Jong-Hoon Oh (2004)
    "A multiplicative up-propagation algorithm,"
    in Proceedings of the International Conference on Machine Learning (ICML-2004),
    pp. 17-24, Banff, Canada, July 4-8, 2004.