One-step pipetting and assembly of encoded chemical-laden microparticles for high-throughput multiplexed bioassays S Eun Chung, J Kim, D Yoon Oh, Y Song, S Hoon Lee, S Min, S Kwon Nature communications 5 (1), 3468, 2014 | 75 | 2014 |
The competition for partners in matching markets Y Kanoria, S Min, P Qian Management Science, 2024 | 15* | 2024 |
Cross-sectional variation of intraday liquidity, cross-impact, and their effect on portfolio execution S Min, C Maglaras, CC Moallemi Operations Research 70 (2), 830-846, 2022 | 15* | 2022 |
Policy gradient optimization of Thompson sampling policies S Min, CC Moallemi, DJ Russo arXiv preprint arXiv:2006.16507, 2020 | 13 | 2020 |
Thompson sampling with information relaxation penalties S Min, C Maglaras, CC Moallemi Advances in neural information processing systems 32, 2019 | 13 | 2019 |
An information-theoretic analysis of nonstationary bandit learning S Min, D Russo International Conference on Machine Learning, 24831-24849, 2023 | 10 | 2023 |
Risk-sensitive optimal execution via a conditional value-at-risk objective S Min, CC Moallemi, C Maglaras arXiv preprint arXiv:2201.11962, 2022 | 2 | 2022 |
Modern Dynamic Programming Approaches to Sequential Decision Making S Min Columbia University, 2021 | 1 | 2021 |
Optofluidic in-situ fabrication of magnetic actuators in microfluidic channels SE Chung, J Kim, S Min, NL Kim, S Kwon Conference on Lasers and Electro-Optics, JWA62, 2010 | 1 | 2010 |
Optimizing Sequential Predictions for Order Execution: a Decision Focused Learning Approach S Kweon, Y Yim, S Min Proceedings of the 5th ACM International Conference on AI in Finance, 719-727, 2024 | | 2024 |
Improving Thompson Sampling via Information Relaxation for Budgeted Multi-armed Bandits W Jeong, S Min arXiv preprint arXiv:2408.15535, 2024 | | 2024 |
IN-SITU FABRICATION AND ACTUATION OF MAGNETIC NANOPARTICLES EMBEDDED MI-CROSTRUCTURES IN MICROFLUIDIC CHANNELS SE Chung, J Kim, S Min, L Kim, S Kwon The Chemical and Biological Microsystems Society, 2009 | | 2009 |
Risk-Sensitive Policy Optimization via Predictive CVaR Policy Gradient JH Kim, S Min Forty-first International Conference on Machine Learning, 0 | | |