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Jungtaek Kim
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Year
Set Transformer: A Framework for Attention-based Permutation-Invariant Neural Networks
J Lee, Y Lee, J Kim, A Kosiorek, S Choi, YW Teh
Proceedings of the Thirty-Sixth International Conference on Machine Learning …, 2019
4882019
Learning to Warm-Start Bayesian Hyperparameter Optimization
J Kim, S Kim, S Choi
arXiv preprint arXiv:1710.06219, 2017
27*2017
Open Set Recognition by Regularizing Classifier with Fake Data Generated by Generative Adversarial Networks
I Jo, J Kim, H Kang, YD Kim, S Choi
Proceedings of the Forty-Third IEEE International Conference on Acoustics …, 2018
232018
On Local Optimizers of Acquisition Functions in Bayesian Optimization
J Kim, S Choi
Proceedings of the European Conference on Machine Learning and Principles …, 2020
112020
BayesO: A Bayesian Optimization Framework in Python
J Kim, S Choi
https://bayeso.org, 2017
92017
Bayesian Optimization over Sets
J Kim, M McCourt, T You, S Kim, S Choi
ICML Workshop on Automated Machine Learning, 2019
8*2019
MxML: Mixture of Meta-Learners for Few-Shot Classification
M Park, J Kim, S Kim, Y Liu, S Choi
arXiv preprint arXiv:1904.05658, 2019
62019
Bayesian Optimization with Approximate Set Kernels
J Kim, M McCourt, T You, S Kim, S Choi
Machine Learning 110 (5), 857-879, 2021
52021
Bootstrapping Neural Processes
J Lee*, Y Lee*, J Kim, E Yang, SJ Hwang, YW Teh
Advances in Neural Information Processing Systems 33, 2020
52020
AutoML Challenge: AutoML Framework Using Random Space Partitioning Optimizer
J Kim, J Jeong, S Choi
ICML Workshop on Automatic Machine Learning, 2016
52016
Automated Machine Learning for Soft Voting in an Ensemble of Tree-based Classifiers
J Kim, S Choi
ICML Workshop on Automatic Machine Learning, 2018
42018
Combinatorial 3D Shape Generation via Sequential Assembly
J Kim, H Chung, M Cho, J Park
NeurIPS Workshop on Machine Learning for Engineering Modeling, Simulation …, 2020
32020
TAEML: Task-Adaptive Ensemble of Meta-Learners
M Park, S Kim, J Kim, Y Liu, S Choi
NeurIPS Workshop on Meta-Learning, 2018
32018
Clustering-Guided GP-UCB for Bayesian Optimization
J Kim, S Choi
Proceedings of the Forty-Third IEEE International Conference on Acoustics …, 2018
32018
Learning to Transfer Initializations for Bayesian Hyperparameter Optimization
J Kim, S Kim, S Choi
NeurIPS Workshop on Bayesian Optimization, 2017
32017
On the Optimal Bit Complexity of Circulant Binary Embedding
S Kim, J Kim, S Choi
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018
22018
On Evaluation Metrics for Graph Generative Models
R Thompson, B Knyazev, E Ghalebi, J Kim, GW Taylor
arXiv preprint arXiv:2201.09871, 2022
12022
Brick-by-Brick: Combinatorial Construction with Deep Reinforcement Learning
H Chung*, J Kim*, B Knyazev, J Lee, GW Taylor, J Park, M Cho
Advances in Neural Information Processing Systems 34, 2021
12021
Learning to Assemble Geometric Shapes
J Lee*, J Kim*, H Chung, J Park, M Cho
arXiv preprint arXiv:2205.11809, 2022
2022
On Uncertainty Estimation by Tree-based Surrogate Models in Sequential Model-based Optimization
J Kim, S Choi
Proceedings of the Twenty-Fifth International Conference on Artificial …, 2022
2022
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Articles 1–20