Min-hwan Oh

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 34

Top Topics

Multi Armed Bandits

Topological Features

Reinforcement Learning

Multinomial Logit

Top Venues

Publications

Joongkyu Lee, Seung Joon Park, Yunhao Tang, Min-hwan Oh
Learning Uncertainty-Aware Temporally-Extended Actions. CoRR (2024)
Kyungbok Lee, Myunghee Cho Paik, Min-hwan Oh, Gi-Soo Kim
Mixed-Effects Contextual Bandits. AAAI (2024)
Byung Hyun Lee, Min-hwan Oh, Se Young Chun
Doubly Perturbed Task Free Continual Learning. AAAI (2024)
Harin Lee, Taehyun Hwang, Min-hwan Oh
Lasso Bandit with Compatibility Condition on Optimal Arm. CoRR (2024)
Jongyeong Lee, Junya Honda, Shinji Ito, Min-hwan Oh
Follow-the-Perturbed-Leader with Fréchet-type Tail Distributions: Optimality in Adversarial Bandits and Best-of-Both-Worlds. CoRR (2024)
Jongyeong Lee, Junya Honda, Shinji Ito, Min-hwan Oh
Follow-the-Perturbed-Leader with Fréchet-type Tail Distributions: Optimality in Adversarial Bandits and Best-of-Both-Worlds. COLT (2024)
Joongkyu Lee, Seung Joon Park, Yunhao Tang, Min-hwan Oh
Learning Uncertainty-Aware Temporally-Extended Actions. AAAI (2024)
Joongkyu Lee, Min-hwan Oh
Demystifying Linear MDPs and Novel Dynamics Aggregation Framework. ICLR (2024)
Wooseong Cho, Taehyun Hwang, Joongkyu Lee, Min-hwan Oh
Randomized Exploration for Reinforcement Learning with Multinomial Logistic Function Approximation. CoRR (2024)
Joongkyu Lee, Min-hwan Oh
Nearly Minimax Optimal Regret for Multinomial Logistic Bandit. CoRR (2024)
Hyun-Jun Choi, Rajan Udwani, Min-hwan Oh
Cascading Contextual Assortment Bandits. NeurIPS (2023)
Byung Hyun Lee, Min-hwan Oh, Se Young Chun
Doubly Perturbed Task-Free Continual Learning. CoRR (2023)
Byeongchan Kim, Min-hwan Oh
Model-based Offline Reinforcement Learning with Count-based Conservatism. CoRR (2023)
Taehyun Hwang, Min-hwan Oh
Model-Based Reinforcement Learning with Multinomial Logistic Function Approximation. AAAI (2023)
Young-Geun Choi, Gi-Soo Kim, Yunseo Choi, Wooseong Cho, Myunghee Cho Paik, Min-hwan Oh
Semi-Parametric Contextual Pricing Algorithm using Cox Proportional Hazards Model. ICML (2023)
Taehyun Hwang, Kyuwook Chai, Min-hwan Oh
Combinatorial Neural Bandits. CoRR (2023)
Jaehun Song, Min-hwan Oh, Hyung-Sin Kim
Personalized Federated Learning with Server-Side Information. CoRR (2022)
Taehyun Hwang, Min-hwan Oh
Model-Based Reinforcement Learning with Multinomial Logistic Function Approximation. CoRR (2022)
Yoon-Sik Cho, Min-hwan Oh
Stochastic-Expert Variational Autoencoder for Collaborative Filtering. WWW (2022)
Wonyoung Kim, Min-hwan Oh, Myunghee Cho Paik
Squeeze All: Novel Estimator and Self-Normalized Bound for Linear Contextual Bandits. CoRR (2022)
Min-hwan Oh, Garud Iyengar
Multinomial Logit Contextual Bandits: Provable Optimality and Practicality. AAAI (2021)
Min-hwan Oh, Garud Iyengar
Multinomial Logit Contextual Bandits: Provable Optimality and Practicality. CoRR (2021)
Min-hwan Oh, Garud Iyengar, Assaf Zeevi
Sparsity-Agnostic Lasso Bandit. ICML (2021)
Min-hwan Oh, Garud Iyengar, Assaf Zeevi
Sparsity-Agnostic Lasso Bandit. CoRR (2020)
Min-hwan Oh, Garud Iyengar
Sequential Anomaly Detection using Inverse Reinforcement Learning. CoRR (2020)
Min-hwan Oh, Peder A. Olsen, Karthikeyan Natesan Ramamurthy
Crowd Counting with Decomposed Uncertainty. AAAI (2020)
Min-hwan Oh, Peder A. Olsen, Karthikeyan Natesan Ramamurthy
Crowd Counting with Decomposed Uncertainty. CoRR (2019)
Min-hwan Oh, Garud Iyengar
Thompson Sampling for Multinomial Logit Contextual Bandits. NeurIPS (2019)
Min-hwan Oh, Garud Iyengar
Sequential Anomaly Detection using Inverse Reinforcement Learning. KDD (2019)
Min-hwan Oh, Peder A. Olsen, Karthikeyan Natesan Ramamurthy
Counting and Segmenting Sorghum Heads. CoRR (2019)
Weiyi Liu, Pin-Yu Chen, Fucai Yu, Toyotaro Suzumura, Guangmin Hu, Hal James Cooper, Min-hwan Oh, Sailung Yeung
Corrections to "Learning Graph Topological Features via GAN". IEEE Access 7 (2019)
Hiroki Kanezashi, Toyotaro Suzumura, Dario Garcia-Gasulla, Min-hwan Oh, Satoshi Matsuoka
Adaptive Pattern Matching with Reinforcement Learning for Dynamic Graphs. HiPC (2018)
Hiroki Kanezashi, Toyotaro Suzumura, Dario Garcia-Gasulla, Min-hwan Oh, Satoshi Matsuoka
Adaptive Pattern Matching with Reinforcement Learning for Dynamic Graphs. CoRR (2018)
Min-hwan Oh, Garud Iyengar
Directed Exploration in PAC Model-Free Reinforcement Learning. CoRR (2018)
Daniel Soudry, Suraj Keshri, Patrick Stinson, Min-hwan Oh, Garud Iyengar, Liam Paninski
Efficient "Shotgun" Inference of Neural Connectivity from Highly Sub-sampled Activity Data. PLoS Comput. Biol. 11 (10) (2015)