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Books and Theses
- 2018
[b1]Chansoo Lee:
Analysis of Perturbation Techniques in Online Learning. University of Michigan, USA, 2018
Journal Articles
- 2024
- [j2]Zi Wang, George E. Dahl, Kevin Swersky, Chansoo Lee, Zachary Nado, Justin Gilmer, Jasper Snoek, Zoubin Ghahramani:
Pre-trained Gaussian Processes for Bayesian Optimization. J. Mach. Learn. Res. 25: 212:1-212:83 (2024) - 2017
- [j1]Ilya Amburg, Krishna Dasaratha, Laure Flapan, Thomas Garrity, Chansoo Lee, Cornelia Mihaila, Nicholas Neumann-Chun, Sarah Peluse, Matthew Stoffregen:
Stern Sequences for a Family of Multidimensional Continued Fractions: TRIP-Stern Sequences. J. Integer Seq. 20(1): 17.1.7 (2017)
Conference and Workshop Papers
- 2024
- [c11]Xingyou Song, Yingtao Tian, Robert Tjarko Lange, Chansoo Lee, Yujin Tang, Yutian Chen:
Position: Leverage Foundational Models for Black-Box Optimization. ICML 2024 - 2023
- [c10]Ashok Cutkosky, Abhimanyu Das, Weihao Kong, Chansoo Lee, Rajat Sen:
Blackbox optimization of unimodal functions. UAI 2023: 476-484 - 2022
- [c9]Xingyou Song, Sagi Perel, Chansoo Lee, Greg Kochanski, Daniel Golovin:
Open Source Vizier: Distributed Infrastructure and API for Reliable and Flexible Blackbox Optimization. AutoML 2022: 8/1-17 - [c8]Yutian Chen, Xingyou Song, Chansoo Lee, Zi Wang, Richard Zhang, David Dohan, Kazuya Kawakami, Greg Kochanski, Arnaud Doucet, Marc'Aurelio Ranzato, Sagi Perel, Nando de Freitas:
Towards Learning Universal Hyperparameter Optimizers with Transformers. NeurIPS 2022 - 2020
- [c7]Daniel Golovin, John Karro, Greg Kochanski, Chansoo Lee, Xingyou Song, Qiuyi (Richard) Zhang:
Gradientless Descent: High-Dimensional Zeroth-Order Optimization. ICLR 2020 - 2019
- [c6]Jacob D. Abernethy, Young Hun Jung, Chansoo Lee, Audra McMillan, Ambuj Tewari:
Online Learning via the Differential Privacy Lens. NeurIPS 2019: 8892-8902 - 2018
- [c5]Ferdinando Fioretto, Chansoo Lee, Pascal Van Hentenryck:
Constrained-Based Differential Privacy for Mobility Services. AAMAS 2018: 1405-1413 - 2016
- [c4]Satyen Kale, Chansoo Lee, Dávid Pál:
Hardness of Online Sleeping Combinatorial Optimization Problems. NIPS 2016: 2181-2189 - 2015
- [c3]Jacob D. Abernethy, Chansoo Lee, Ambuj Tewari:
Fighting Bandits with a New Kind of Smoothness. NIPS 2015: 2197-2205 - 2014
- [c2]Jacob D. Abernethy, Chansoo Lee, Abhinav Sinha, Ambuj Tewari:
Online Linear Optimization via Smoothing. COLT 2014: 807-823 - 2013
- [c1]Kihyuk Sohn, Guanyu Zhou, Chansoo Lee, Honglak Lee:
Learning and Selecting Features Jointly with Point-wise Gated Boltzmann Machines. ICML (2) 2013: 217-225
Informal and Other Publications
- 2024
- [i13]Xingyou Song, Oscar Li, Chansoo Lee, Bangding Yang, Daiyi Peng, Sagi Perel, Yutian Chen:
OmniPred: Language Models as Universal Regressors. CoRR abs/2402.14547 (2024) - [i12]Xingyou Song, Yingtao Tian, Robert Tjarko Lange, Chansoo Lee, Yujin Tang, Yutian Chen:
Position: Leverage Foundational Models for Black-Box Optimization. CoRR abs/2405.03547 (2024) - [i11]Xingyou Song, Qiuyi Zhang, Chansoo Lee, Emily Fertig, Tzu-Kuo Huang, Lior Belenki, Greg Kochanski, Setareh Ariafar, Srinivas Vasudevan, Sagi Perel, Daniel Golovin:
The Vizier Gaussian Process Bandit Algorithm. CoRR abs/2408.11527 (2024) - 2022
- [i10]Yutian Chen, Xingyou Song, Chansoo Lee, Zi Wang, Qiuyi Zhang, David Dohan, Kazuya Kawakami, Greg Kochanski, Arnaud Doucet, Marc'Aurelio Ranzato, Sagi Perel, Nando de Freitas:
Towards Learning Universal Hyperparameter Optimizers with Transformers. CoRR abs/2205.13320 (2022) - [i9]Zi Wang, George E. Dahl, Kevin Swersky, Chansoo Lee, Zelda Mariet, Zachary Nado, Justin Gilmer, Jasper Snoek, Zoubin Ghahramani:
Pre-training helps Bayesian optimization too. CoRR abs/2207.03084 (2022) - [i8]Xingyou Song, Sagi Perel, Chansoo Lee, Greg Kochanski, Daniel Golovin:
Open Source Vizier: Distributed Infrastructure and API for Reliable and Flexible Blackbox Optimization. CoRR abs/2207.13676 (2022) - [i7]Jonathan Lorraine, Nihesh Anderson, Chansoo Lee, Quentin de Laroussilhe, Mehadi Hassen:
Task Selection for AutoML System Evaluation. CoRR abs/2208.12754 (2022) - 2021
- [i6]Zi Wang, George E. Dahl, Kevin Swersky, Chansoo Lee, Zelda Mariet, Zachary Nado, Justin Gilmer, Jasper Snoek, Zoubin Ghahramani:
Automatic prior selection for meta Bayesian optimization with a case study on tuning deep neural network optimizers. CoRR abs/2109.08215 (2021) - 2019
- [i5]Daniel Golovin, John Karro, Greg Kochanski, Chansoo Lee, Xingyou Song, Qiuyi (Richard) Zhang:
Gradientless Descent: High-Dimensional Zeroth-Order Optimization. CoRR abs/1911.06317 (2019) - 2017
- [i4]Jacob D. Abernethy, Chansoo Lee, Audra McMillan, Ambuj Tewari:
Online Learning via Differential Privacy. CoRR abs/1711.10019 (2017) - 2015
- [i3]Satyen Kale, Chansoo Lee, Dávid Pál:
Hardness of Online Sleeping Combinatorial Optimization Problems. CoRR abs/1509.03600 (2015) - [i2]Jacob D. Abernethy, Chansoo Lee, Ambuj Tewari:
Fighting Bandits with a New Kind of Smoothness. CoRR abs/1512.04152 (2015) - 2014
- [i1]Jacob D. Abernethy, Chansoo Lee, Abhinav Sinha, Ambuj Tewari:
Online Linear Optimization via Smoothing. CoRR abs/1405.6076 (2014)
Coauthor Index
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