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2020 – today
- 2024
[c9]Guy Tennenholtz, Yinlam Chow, Chih-Wei Hsu, Jihwan Jeong, Lior Shani, Azamat Tulepbergenov, Deepak Ramachandran, Martin Mladenov, Craig Boutilier:
Demystifying Embedding Spaces using Large Language Models. ICLR 2024- 2023
- [c8]Jihwan Jeong, Scott Sanner, Akshat Kumar:
A Mixed-Integer Linear Programming Reduction of Disjoint Bilinear Programs via Symbolic Variable Elimination. CPAIOR 2023: 79-95 - [c7]Jihwan Jeong, Xiaoyu Wang, Michael Gimelfarb, Hyunwoo Kim, Baher Abdulhai, Scott Sanner:
Conservative Bayesian Model-Based Value Expansion for Offline Policy Optimization. ICLR 2023 - [i7]Guy Tennenholtz, Yinlam Chow, Chih-Wei Hsu, Jihwan Jeong, Lior Shani, Azamat Tulepbergenov, Deepak Ramachandran, Martin Mladenov, Craig Boutilier:
Demystifying Embedding Spaces using Large Language Models. CoRR abs/2310.04475 (2023) - [i6]Jihwan Jeong, Yinlam Chow, Guy Tennenholtz, Chih-Wei Hsu, Azamat Tulepbergenov, Mohammad Ghavamzadeh, Craig Boutilier:
Factual and Personalized Recommendations using Language Models and Reinforcement Learning. CoRR abs/2310.06176 (2023) - 2022
- [j2]Zheda Mai
, Ruiwen Li, Jihwan Jeong, David Quispe, Hyunwoo Kim, Scott Sanner:
Online continual learning in image classification: An empirical survey. Neurocomputing 469: 28-51 (2022) - [c6]Noah Patton, Jihwan Jeong, Mike Gimelfarb, Scott Sanner:
A Distributional Framework for Risk-Sensitive End-to-End Planning in Continuous MDPs. AAAI 2022: 9894-9901 - [c5]Jihwan Jeong, Parth Jaggi, Andrew Butler, Scott Sanner:
An Exact Symbolic Reduction of Linear Smart Predict+Optimize to Mixed Integer Linear Programming. ICML 2022: 10053-10067 - [i5]Jihwan Jeong, Xiaoyu Wang, Michael Gimelfarb, Hyunwoo Kim, Baher Abdulhai, Scott Sanner:
Conservative Bayesian Model-Based Value Expansion for Offline Policy Optimization. CoRR abs/2210.03802 (2022) - 2021
- [j1]Jihwan Jeong, Hayong Shin:
Bayesian optimization for a multiple-component system with target values. Comput. Ind. Eng. 157: 107310 (2021) - [c4]Dongsub Shim, Zheda Mai, Jihwan Jeong, Scott Sanner, Hyunwoo Kim, Jongseong Jang:
Online Class-Incremental Continual Learning with Adversarial Shapley Value. AAAI 2021: 9630-9638 - [c3]Jihwan Jeong, Parth Jaggi, Scott Sanner:
Symbolic Dynamic Programming for Continuous State MDPs with Linear Program Transitions. IJCAI 2021: 4083-4089 - [i4]Zheda Mai, Ruiwen Li, Jihwan Jeong, David Quispe, Hyunwoo Kim, Scott Sanner:
Online Continual Learning in Image Classification: An Empirical Survey. CoRR abs/2101.10423 (2021) - [i3]Noah Patton, Jihwan Jeong, Michael Gimelfarb, Scott Sanner:
RAPTOR: End-to-end Risk-Aware MDP Planning and Policy Learning by Backpropagation. CoRR abs/2106.07260 (2021) - 2020
- [i2]Zheda Mai, Hyunwoo Kim, Jihwan Jeong, Scott Sanner:
Batch-level Experience Replay with Review for Continual Learning. CoRR abs/2007.05683 (2020) - [i1]Zheda Mai, Dongsub Shim, Jihwan Jeong, Scott Sanner, Hyunwoo Kim, Jongseong Jang:
Adversarial Shapley Value Experience Replay for Task-Free Continual Learning. CoRR abs/2009.00093 (2020)
2010 – 2019
- 2014
- [c2]Jonghoon Kwon, Jihwan Jeong, Jehyun Lee, Heejo Lee:
DroidGraph: discovering Android malware by analyzing semantic behavior. CNS 2014: 498-499 - [c1]Jihwan Jeong, Dongwon Seo, Chanyoung Lee, Jonghoon Kwon, Heejo Lee, John Milburn:
MysteryChecker: Unpredictable attestation to detect repackaged malicious applications in Android. MALWARE 2014: 50-57
Coauthor Index
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