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Min-hwan Oh

Observed names: Min-Hwan Oh, Oh, Min Hwan, Oh, Min-hwan
ORCID: 0000-0003-2137-2762
Observed ORCID: 0000-0003-2137-2762
OpenAlex ID: A5006205893
Crowd Counting with Decomposed Uncertainty
2020 · Oh, Min-hwan, Olsen, Peder, et al. · AAAI Publications (The Association for the Advancement of Artificial Intelligence (AAAI)) · 107
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Sequential Anomaly Detection using Inverse Reinforcement Learning
2019 · Min-hwan Oh, Garud Iyengar · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · 95
Efficient "Shotgun" Inference of Neural Connectivity from Highly Sub-sampled Activity Data
2015 · Daniel Soudry, Suraj Keshri, et al. · PLoS Computational Biology · 67
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Thompson Sampling for Multinomial Logit Contextual Bandits
2019 · Min-hwan Oh, Garud Iyengar · Seoul National University Open Repository (Seoul National University) · 21
Multinomial Logit Contextual Bandits: Provable Optimality and Practicality
2021 · Min-hwan Oh, Garud Iyengar · Proceedings of the AAAI Conference on Artificial Intelligence · 19
Stochastic-Expert Variational Autoencoder for Collaborative Filtering
2022 · Yoon-Sik Cho, Min-hwan Oh · International World Wide Web Conference (WWW) · 17
Counting and Segmenting Sorghum Heads
2019 · Oh, Min-hwan, Olsen, Peder, et al. · arXiv (Cornell University) · 17
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Crowd Counting with Decomposed Uncertainty
2020 · Min-hwan Oh, Peder Olsen, et al. · Proceedings of the AAAI Conference on Artificial Intelligence · 15
Sparsity-Agnostic Lasso Bandit
2020 · Oh, Min-hwan, Iyengar, Garud, et al. · arXiv (Cornell University) · 14
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Personalized Federated Learning With Server-Side Information
2022 · Jaehun Song, Min-Hwan Oh, et al. · IEEE Access · 10
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Automatic event detection in basketball using HMM with energy based defensive assignment
2019 · Suraj Keshri, Min-hwan Oh, et al. · Journal of Quantitative Analysis in Sports · 10
Improved Online Confidence Bounds for Multinomial Logistic Bandits
2025 · Lee, Joongkyu, Oh, Min-hwan · arXiv (Cornell University) · 9
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Nearly Minimax Optimal Regret for Multinomial Logistic Bandit
2024 · Joongkyu Lee, Min-Hwan Oh · neural information processing systems · 9
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Directed Exploration in PAC Model-Free Reinforcement Learning
2018 · Oh, Min-hwan, Iyengar, Garud · arXiv (Cornell University) · 7
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Model-based Offline Reinforcement Learning with Count-based Conservatism
2023 · Kim, Byeongchan, Oh, Min-hwan · arXiv (Cornell University) · 5
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Model-Based Reinforcement Learning with Multinomial Logistic Function Approximation
2023 · Taehyun Hwang, Min-hwan Oh · Proceedings of the AAAI Conference on Artificial Intelligence · 5
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Can GAN Learn Topological Features of a Graph?
2017 · Liu, Weiyi, Chen, Pin-Yu, et al. · arXiv (Cornell University) · 5
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Dynamic Assortment Selection and Pricing with Censored Preference Feedback
2025 · Kim, Jung-hun, Oh, Min-hwan · arXiv (Cornell University) · 4
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Linear Bandits with Partially Observable Features
2025 · Kim, Wonyoung, Park, Sungwoo, et al. · arXiv (Cornell University) · 4
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Doubly Perturbed Task Free Continual Learning
2024 · Byung Hyun Lee, Min-hwan Oh, et al. · Proceedings of the AAAI Conference on Artificial Intelligence · 4
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Bridging the Gap Between Self-Report and Behavioral Laboratory Measures: A Real-Time Driving Task With Inverse Reinforcement Learning
2024 · Sang Ho Lee, Myeong Seop Song, et al. · Psychological Science · 4
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Lasso Bandit with Compatibility Condition on Optimal Arm
2024 · Lee, Harin, Hwang, Taehyun, et al. · arXiv (Cornell University) · 3
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Follow-the-Perturbed-Leader with Fréchet-type Tail Distributions: Optimality in Adversarial Bandits and Best-of-Both-Worlds
2024 · Lee, Jongyeong, Honda, Junya, et al. · arXiv (Cornell University) · 3
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Local Anti-Concentration Class: Logarithmic Regret for Greedy Linear Contextual Bandit
2024 · Seok-Jin Kim, Min-Hwan Oh · neural information processing systems · 3
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Queueing Matching Bandits with Preference Feedback
2024 · Jung-Hun Kim, Min-Hwan Oh · neural information processing systems · 3
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Works count: 53
Citation count: 485
H-index: 10
I10-index: 11
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