Chansoo Lee

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 17

Top Topics

Differential Privacy

Differentially Private

Top Venues

Publications

Xingyou Song, Oscar Li, Chansoo Lee, Bangding Yang, Daiyi Peng, Sagi Perel, Yutian Chen
OmniPred: Language Models as Universal Regressors. CoRR (2024)
Xingyou Song, Yingtao Tian, Robert Tjarko Lange, Chansoo Lee, Yujin Tang, Yutian Chen
Position: Leverage Foundational Models for Black-Box Optimization. CoRR (2024)
Ashok Cutkosky, Abhimanyu Das, Weihao Kong, Chansoo Lee, Rajat Sen
Blackbox optimization of unimodal functions. UAI (2023)
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)
Xingyou Song, Sagi Perel, Chansoo Lee, Greg Kochanski, Daniel Golovin
Open Source Vizier: Distributed Infrastructure and API for Reliable and Flexible Blackbox Optimization. CoRR (2022)
Jonathan Lorraine, Nihesh Anderson, Chansoo Lee, Quentin de Laroussilhe, Mehadi Hassen
Task Selection for AutoML System Evaluation. CoRR (2022)
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 (2022)
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)
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 (2022)
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 (2021)
Daniel Golovin, John Karro, Greg Kochanski, Chansoo Lee, Xingyou Song, Qiuyi Zhang
Gradientless Descent: High-Dimensional Zeroth-Order Optimization. ICLR (2020)
Jacob D. Abernethy, Young Hun Jung, Chansoo Lee, Audra McMillan, Ambuj Tewari
Online Learning via the Differential Privacy Lens. NeurIPS (2019)
Daniel Golovin, John Karro, Greg Kochanski, Chansoo Lee, Xingyou Song, Qiuyi Zhang
Gradientless Descent: High-Dimensional Zeroth-Order Optimization. CoRR (2019)
Ferdinando Fioretto, Chansoo Lee, Pascal Van Hentenryck
Constrained-Based Differential Privacy for Mobility Services. AAMAS (2018)
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) (2017)
Jacob D. Abernethy, Chansoo Lee, Audra McMillan, Ambuj Tewari
Online Learning via Differential Privacy. CoRR (2017)
Satyen Kale, Chansoo Lee, Dávid Pál
Hardness of Online Sleeping Combinatorial Optimization Problems. NIPS (2016)
Jacob D. Abernethy, Chansoo Lee, Ambuj Tewari
Fighting Bandits with a New Kind of Smoothness. CoRR (2015)
Satyen Kale, Chansoo Lee, Dávid Pál
Hardness of Online Sleeping Combinatorial Optimization Problems. CoRR (2015)
Jacob D. Abernethy, Chansoo Lee, Ambuj Tewari
Fighting Bandits with a New Kind of Smoothness. NIPS (2015)
Jacob D. Abernethy, Chansoo Lee, Abhinav Sinha, Ambuj Tewari
Online Linear Optimization via Smoothing. CoRR (2014)
Jacob D. Abernethy, Chansoo Lee, Abhinav Sinha, Ambuj Tewari
Online Linear Optimization via Smoothing. COLT (2014)
Kihyuk Sohn, Guanyu Zhou, Chansoo Lee, Honglak Lee
Learning and Selecting Features Jointly with Point-wise Gated Boltzmann Machines. ICML (2) (2013)