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Combinatorial Bayesian Optimization with Random Mapping Functions to Convex Polytope

Nov 26, 2020
Jungtaek Kim, Minsu Cho, Seungjin Choi

* 10 pages, 2 figures 

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Sparse Network Inversion for Key Instance Detection in Multiple Instance Learning

Sep 08, 2020
Beomjo Shin, Junsu Cho, Hwanjo Yu, Seungjin Choi

* 8 pages, 4 figures, in Proceedings of the 25th International Conference on Pattern Recognition (ICPR-2020) 

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Neural Complexity Measures

Aug 07, 2020
Yoonho Lee, Juho Lee, Sung Ju Hwang, Eunho Yang, Seungjin Choi


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Discrete Infomax Codes for Meta-Learning

May 28, 2019
Yoonho Lee, Wonjae Kim, Seungjin Choi

* 16 pages 

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Bayesian Optimization over Sets

May 23, 2019
Jungtaek Kim, Michael McCourt, Tackgeun You, Saehoon Kim, Seungjin Choi

* 14 pages, 4 figures, 3 tables 

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Practical Bayesian Optimization with Threshold-Guided Marginal Likelihood Maximization

May 18, 2019
Jungtaek Kim, Seungjin Choi

* 7 pages 

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MxML: Mixture of Meta-Learners for Few-Shot Classification

Apr 11, 2019
Minseop Park, Jungtaek Kim, Saehoon Kim, Yanbin Liu, Seungjin Choi

* 12 pages 

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On Local Optimizers of Acquisition Functions in Bayesian Optimization

Jan 24, 2019
Jungtaek Kim, Seungjin Choi

* 20 pages, 2 figures 

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Learning to Warm-Start Bayesian Hyperparameter Optimization

Oct 31, 2018
Jungtaek Kim, Saehoon Kim, Seungjin Choi

* 14 pages, a preliminary version was presented at NIPS 2017 workshop on Bayesian optimization 

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A Bayesian model for sparse graphs with flexible degree distribution and overlapping community structure

Oct 03, 2018
Juho Lee, Lancelot F. James, Seungjin Choi, François Caron


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Set Transformer

Oct 01, 2018
Juho Lee, Yoonho Lee, Jungtaek Kim, Adam R. Kosiorek, Seungjin Choi, Yee Whye Teh


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Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace

Jun 14, 2018
Yoonho Lee, Seungjin Choi

* Accepted to ICML 2018 

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Bayesian inference on random simple graphs with power law degree distributions

Jun 18, 2017
Juho Lee, Creighton Heaukulani, Zoubin Ghahramani, Lancelot F. James, Seungjin Choi


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Learning to Select Pre-Trained Deep Representations with Bayesian Evidence Framework

Apr 25, 2016
Yong-Deok Kim, Taewoong Jang, Bohyung Han, Seungjin Choi

* Appearing in CVPR-2016 (oral presentation) 

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Gaussian Copula Variational Autoencoders for Mixed Data

Apr 18, 2016
Suwon Suh, Seungjin Choi

* 21 pages 

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Tree-Guided MCMC Inference for Normalized Random Measure Mixture Models

Nov 18, 2015
Juho Lee, Seungjin Choi

* 12 pages, 10 figures, NIPS-2015 

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Bayesian Hierarchical Clustering with Exponential Family: Small-Variance Asymptotics and Reducibility

Jun 03, 2015
Juho Lee, Seungjin Choi

* 10 pages, 2 figures, AISTATS-2015 

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Bilinear Random Projections for Locality-Sensitive Binary Codes

Jun 03, 2015
Saehoon Kim, Seungjin Choi

* 11 pages, 23 figures, CVPR-2015 

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Convex Optimization for Binary Classifier Aggregation in Multiclass Problems

Jan 16, 2014
Sunho Park, TaeHyun Hwang, Seungjin Choi

* Appeared in Proceedings of the 2014 SIAM International Conference on Data Mining (SDM 2014) 

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Regularized Discriminant Embedding for Visual Descriptor Learning

Jan 16, 2013
Kye-Hyeon Kim, Rui Cai, Lei Zhang, Seungjin Choi

* 3 pages + 1 additional page containing only cited references; The full version of this manuscript is currently under review in an international journal 

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Learning Features with Structure-Adapting Multi-view Exponential Family Harmoniums

Jan 16, 2013
Yoonseop Kang, Seungjin Choi

* 3 pages, 2 figures, ICLR2013 workshop track submission 

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