Publications

Jihwan Jeong, Xiaoyu Wang, Michael Gimelfarb, Hyunwoo Kim, Baher Abdulhai, Scott Sanner (2023). Conservative Bayesian Model-Based Value Expansion for Offline Policy Optimization. In ICLR-23.

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Jihwan Jeong, Parth Jaggi, Andrew Butler, Scott Sanner (2022). An Exact Symbolic Reduction of Linear Smart Predict+Optimize to Mixed Integer Linear Programming. In ICML-22.

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Noah Patton, Jihwan Jeong, Mike Gimelfarb, Scott Sanner (2022). A Distributional Framework for Risk-Sensitive End-to-End Planning in Continuous MDPs. In AAAI-22.

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Zheda Mai, Ruiwen Li, Jihwan Jeong, David Quispe, Hyunwoo Kim, Scott Sanner (2022). Online Continual Learning in Image Classification: An Empirical Survey. Neurocomputing, 469: 28-51, 2022.

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Jihwan Jeong, Parth Jaggi, Scott Sanner (2021). Symbolic Dynamic Programming for Continuous State MDPs with Linear Program Transitions. In IJCAI-21.

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Jihwan Jeong, Hayong Shin (2021). Bayesian Optimization for a Multiple-Component System with Target Values. Computers & Industrial Engineering, 157.

Dongsub Shim, Zheda Mai, Jihwan Jeong, Scott Sanner, Hyunwoo Kim, Jongseong Jang (2021). Online Class-Incremental Continual Learning with Adversarial Shapley Value. In AAAI-21.

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Zheda Mai, Hyunwoo Kim, Jihwan Jeong, Scott Sanner (2020). Batch-level Experience Replay with Review for Continual Learning. In CVPR Workshop on Continual Learning in Computer Vision.

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