NEWS | JUNGTAEK KIM

JUNGTAEK KIM

Postdoctoral Research Associate
at the University of Wisconsin–Madison

jungtaek.kim [at] wisc [dot] edu

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NEWS

[July 2024] My collaborative work "Exploiting Preferences in Loss Functions for Sequential Recommendation via Weak Transitivity" has been accepted at CIKM-2024.
[May 2024] My work "Noise-Adaptive Confidence Sets for Linear Bandits and Application to Bayesian Optimization" with Prof. Kwang-Sung Jun has been accepted at ICML-2024.
[February 2024] My new paper "Noise-Adaptive Confidence Sets for Linear Bandits and Application to Bayesian Optimization" has been released at arXiv.
[January 2024] I will serve as a reviewer for UAI-2024.
[January 2024] My paper "Generalized Neural Sorting Networks with Error-Free Differentiable Swap Functions" with Jeongbeen Yoon and Prof. Minsu Cho has been accepted at ICLR-2024.
[January 2024] My new paper "Beyond Regrets: Geometric Metrics for Bayesian Optimization" is released at arXiv.
[January 2024] Happy new year!
[December 2023] I will serve as a reviewer for ICML-2024.
[November 2023] My paper "Multi-BOWS: Multi-Fidelity Multi-Objective Bayesian Optimization with Warm Starts for Nanophotonic Structure Design" with Mingxuan Li, Yirong Li, Prof. Andrés Gómez, Prof. Oliver Hinder, and Prof. Paul W. Leu has been accepted at RSC Digital Discovery.
[October 2023] My papers "Datasets and Benchmarks for Nanophotonic Structure and Parametric Design Simulations" and "Generative Neural Fields by Mixtures of Neural Implicit Functions" have been released at arXiv.
[October 2023] My collaborative paper with Chaeyun Jang, Hyungi Lee, and Prof. Juho Lee has been accepted at the 3rd NeurIPS Workshop on Efficient Natural Language and Speech Processing.
[October 2023] My new paper with Hyunsoo Chung has been accepted at the NeurIPS 2023 Workshop on Self-Supervised Learning - Theory and Practice.
[October 2023] My new paper "Generalized Neural Sorting Networks with Error-Free Differentiable Swap Functions" with Jeongbeen Yoon and Prof. Minsu Cho has been released at arXiv.
[October 2023] My paper "BayesO: A Bayesian Optimization Framework in Python" was published in the Journal of Open Source Software.
[September 2023] Two papers have been accepted at NeurIPS-2023. One paper with Tackgeun You, Mijeong Kim, and Prof. Bohyung Han will be presented at the main track of NeurIPS-2023 and another paper with Mingxuan Li, Prof. Oliver Hinder, and Prof. Paul W. Leu will be presented at the datasets and benchmarks track of NeurIPS-2023.
[August 2023] I will serve as a reviewer for ICLR-2024.
[August 2023] I will serve as a reviewer for AISTATS-2024.
[July 2023] I am invited to BIRS Workshop on 3D Generative Models, which will be held in the Banff International Research Station from July 9 to July 14, 2023. I will give a talk "Combinatorial 3D Shape Assembly with LEGO Bricks" at the workshop.
[July 2023] My new website is available now. I will keep updating this profile page for my own purpose.
[May 2023] My new paper "Density Ratio Estimation-based Bayesian Optimization with Semi-Supervised Learning" is available at arXiv now.
[May 2023] I will give a talk at the minisymposium "Sequential Decision Making for Optimization, Learning and Search", which will be held as part of the 10th International Congress on Industrial and Applied Mathematics (ICIAM-2023).
[March 2023] I will serve as a reviewer for NeurIPS-2023.
[January 2023] I will serve as a reviewer for ICML-2023.
[January 2023] Happy new year!
[December 2022] I will serve as a program committee member for UAI-2023.
[November 2022] I will serve as a reviewer for CVPR-2023.
[October 2022] My new paper "Sequential Brick Assembly with Efficient Constraint Satisfaction" (with Seokjun Ahn, Prof. Minsu Cho, and Prof. Jaesik Park) is available at arXiv now.
[August 2022] I will serve as a reviewer for AISTATS-2023.
[July 2022] I will serve as a reviewer for ICLR-2023.
[July 2022] I will serve as a program committee member for AAAI-2023.
[July 2022] I joined the University of Pittsburgh as a postdoctoral associate, and I will work with Prof. Paul W. Leu, Prof. Satish Iyengar, Prof. Lucas Mentch, and Prof. Oliver Hinder.
[June 2022] The up-to-date version of my work "Combinatorial Bayesian Optimization with Random Mapping Functions to Convex Polytopes" is available at arXiv now.
[June 2022] My recent work "Learning to Assemble Geometric Shapes" is available at arXiv now.
[May 2022] My work "Combinatorial Bayesian Optimization with Random Mapping Functions to Convex Polytopes" (with Seungjin Choi and Minsu Cho) has been accepted at UAI-2022.
[May 2022] I will serve as a program committee member for ACML-2022.
[April 2022] My work "Learning to Assemble Geometric Shapes" (with Jinhwi Lee, Hyunsoo Chung, Jaesik Park, and Minsu Cho) has been accepted at IJCAI-ECAI-2022.
[March 2022] I will serve as a reviewer for NeurIPS-2022.
[February 2022] I will serve as a reviewer for a new machine learning journal, Transactions on Machine Learning Research.
[February 2022] I will deliver a lecture, entitled "Recent Trends in Machine Learning: A Large-Scale Perspective," with Kakao Brain this semester at POSTECH.
[February 2022] My work "On Uncertainty Estimation by Tree-based Surrogate Models in Sequential Model-based Optimization" is now on arXiv.
[February 2022] I will start working as a postdoctoral researcher at the Computer Vision Lab, POSTECH under the supervision of Prof. Minsu Cho.
[January 2022] My recent work "On Evaluation Metrics for Graph Generative Models" is available at arXiv.
[January 2022] The recent work "On Evaluation Metrics for Graph Generative Models" (with Rylee Thompson, Boris Knyazev, Elahe Ghalebi, and Graham W. Taylor) has been accepted at ICLR-2022.
[January 2022] My paper "On Uncertainty Estimation by Tree-based Surrogate Models in Sequential Model-based Optimization" is accepted at AISTATS-2022.
[January 2022] I will serve as a reviewer for AutoML-Conf-2022.
[January 2022] Happy new year!
[December 2021] I have succesfully defended my doctoral dissertation. Thanks to my committee, Prof. Minsu Cho, Prof. Seungjin Choi, Prof. Dongwoo Kim, Dr. Michael McCourt, Prof. Jungseul Ok. Look at the photo we took after the defense.
[December 2021] I will serve as a program committee member for UAI-2022.
[December 2021] I will serve as a reviewer for ICML-2022.
[December 2021] Brick-by-Brick is featured in the NeurIPS-2021 recapitulation of Vector Institute as the headline of the article.
[November 2021] I am serving as a reviewer for the Journal of Artificial Intelligence Research (JAIR).
[November 2021] My paper "Brick-by-Brick: Combinatorial Construction with Deep Reinforcement Learning" is now on arXiv.
[September 2021] My work "Brick-by-Brick: Combinatorial Construction with Deep Reinforcement Learning" (with Hyunsoo Chung, Boris Knyazev, Jinhwi Lee, Graham W. Taylor, Jaesik Park, and Minsu Cho) has been accepted at NeurIPS-2021.
[August 2021] I will serve as a reviewer for AAAI-2022.
[July 2021] I will serve as a reviewer for AISTATS-2022.
[July 2021] I will serve as a program committee member for IJCAI-ECAI-2022.
[June 2021] I will serve as a reviewer for ICLR-2022.
[June 2021] I am serving as a reviewer for NeurIPS-2021.
[April 2021] I will serve as a program committee member for the 8th ICML Workshop on Automated Machine Learning (AutoML-2021).
[April 2021] I am serving as a reviewer for the Journal of Open Source Software (JOSS).
[April 2021] I released BayesO v0.5.0 and BayesO Benchmarks v0.1.4.
[April 2021] I will serve as a program committee member for ACML-2021.
[March 2021] My work "Bayesian Optimization with Approximate Set Kernels" is available now.
[January 2021] My work "Bayesian Optimization with Approximate Set Kernels" (with Michael McCourt, Tackgeun You, Saehoon Kim, and Seungjin Choi) will be appeared in Machine Learning Journal as part of Special Issue of the ECML-PKDD-2021 Journal Track.
[January 2021] Happy new year to all of you!
[December 2020] I will serve as a reviewer for ICML-2021.
[December 2020] I released version 0.4.3 of BayesO.
[November 2020] My work, Combinatorial Bayesian Optimization with Random Mapping Functions to Convex Polytope (with Minsu Cho and Seungjin Choi) is released on arXiv.
[November 2020] My recent project, Combinatorial-3D-Shape-Generation and its subordinate project, Geometric-Primitives are made publicly available on GitHub.
[November 2020] I will give a tutorial on Bayesian optimization (with Seungjin Choi) at KSC-2020.
[October 2020] My work "Combinatorial 3D Shape Generation via Sequential Assembly" has been accepted at NeurIPS Workshop on Machine Learning for Engineering Modeling, Simulation, and Design (ML4Eng-2020).
[October 2020] My work "Fragment Relation Networks for Geometric Shape Assembly" has been accepted at NeurIPS Workshop on Learning Meets Combinatorial Algorithms (LMCA-2020).
[October 2020] I am serving as a program committee member for UAI-2021.
[October 2020] I will start working as a (remote) research intern at the Vector Institute under the supervision of Dr. Graham W. Taylor.
[October 2020] I am serving as a reviewer for AISTATS-2021.
[September 2020] The recent work "Bootstrapping Neural Processes" has been accepted at NeurIPS-2020.
[August 2020] I am serving as a program committee member for IJCAI-2021.
[August 2020] I am serving as a program committee member for AAAI-2021.
[June 2020] The paper "On Local Optimizers of Acquisition Functions in Bayesian Optimization" has been accepted at ECML-PKDD-2020.

Last updated: May 1, 2025