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2020 – today
- 2024
[c18]Byung Hyun Lee, Min-hwan Oh, Se Young Chun:
Doubly Perturbed Task Free Continual Learning. AAAI 2024: 13346-13354- [c17]Joongkyu Lee, Seung Joon Park, Yunhao Tang, Min-hwan Oh:
Learning Uncertainty-Aware Temporally-Extended Actions. AAAI 2024: 13391-13399 - [c16]Kyungbok Lee
, Myunghee Cho Paik, Min-hwan Oh, Gi-Soo Kim:
Mixed-Effects Contextual Bandits. AAAI 2024: 13409-13417 - [c15]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: 3375-3430 - [c14]Joongkyu Lee, Min-hwan Oh:
Demystifying Linear MDPs and Novel Dynamics Aggregation Framework. ICLR 2024 - [i19]Joongkyu Lee, Seung Joon Park, Yunhao Tang, Min-hwan Oh:
Learning Uncertainty-Aware Temporally-Extended Actions. CoRR abs/2402.05439 (2024) - [i18]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 abs/2403.05134 (2024) - [i17]Joongkyu Lee, Min-hwan Oh:
Nearly Minimax Optimal Regret for Multinomial Logistic Bandit. CoRR abs/2405.09831 (2024) - [i16]Wooseong Cho, Taehyun Hwang, Joongkyu Lee, Min-hwan Oh:
Randomized Exploration for Reinforcement Learning with Multinomial Logistic Function Approximation. CoRR abs/2405.20165 (2024) - [i15]Harin Lee, Taehyun Hwang, Min-hwan Oh:
Lasso Bandit with Compatibility Condition on Optimal Arm. CoRR abs/2406.00823 (2024) - 2023
- [c13]Taehyun Hwang, Min-hwan Oh:
Model-Based Reinforcement Learning with Multinomial Logistic Function Approximation. AAAI 2023: 7971-7979 - [c12]Wonyoung Kim, Myunghee Cho Paik, Min-hwan Oh:
Squeeze All: Novel Estimator and Self-Normalized Bound for Linear Contextual Bandits. AISTATS 2023: 3098-3124 - [c11]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: 5771-5786 - [c10]Taehyun Hwang, Kyuwook Chai, Min-hwan Oh:
Combinatorial Neural Bandits. ICML 2023: 14203-14236 - [c9]Byeongchan Kim, Min-hwan Oh:
Model-based Offline Reinforcement Learning with Count-based Conservatism. ICML 2023: 16728-16746 - [c8]Hyun-Jun Choi, Rajan Udwani, Min-hwan Oh:
Cascading Contextual Assortment Bandits. NeurIPS 2023 - [i14]Taehyun Hwang, Kyuwook Chai, Min-hwan Oh:
Combinatorial Neural Bandits. CoRR abs/2306.00242 (2023) - [i13]Byeongchan Kim, Min-hwan Oh:
Model-based Offline Reinforcement Learning with Count-based Conservatism. CoRR abs/2307.11352 (2023) - [i12]Byung Hyun Lee, Min-hwan Oh, Se Young Chun:
Doubly Perturbed Task-Free Continual Learning. CoRR abs/2312.13027 (2023) - 2022
- [j3]Jaehun Song, Min Hwan Oh, Hyung-Sin Kim:
Personalized Federated Learning With Server-Side Information. IEEE Access 10: 120245-120255 (2022) - [c7]Yoon-Sik Cho, Min-hwan Oh:
Stochastic-Expert Variational Autoencoder for Collaborative Filtering. WWW 2022: 2482-2490 - [i11]Jaehun Song, Min-hwan Oh, Hyung-Sin Kim:
Personalized Federated Learning with Server-Side Information. CoRR abs/2205.11044 (2022) - [i10]Wonyoung Kim, Min-hwan Oh, Myunghee Cho Paik:
Squeeze All: Novel Estimator and Self-Normalized Bound for Linear Contextual Bandits. CoRR abs/2206.05404 (2022) - [i9]Taehyun Hwang, Min-hwan Oh:
Model-Based Reinforcement Learning with Multinomial Logistic Function Approximation. CoRR abs/2212.13540 (2022) - 2021
- [c6]Min-hwan Oh, Garud Iyengar:
Multinomial Logit Contextual Bandits: Provable Optimality and Practicality. AAAI 2021: 9205-9213 - [c5]Min-hwan Oh, Garud Iyengar, Assaf Zeevi:
Sparsity-Agnostic Lasso Bandit. ICML 2021: 8271-8280 - [i8]Min-hwan Oh, Garud Iyengar:
Multinomial Logit Contextual Bandits: Provable Optimality and Practicality. CoRR abs/2103.13929 (2021) - 2020
- [c4]Min-hwan Oh, Peder A. Olsen, Karthikeyan Natesan Ramamurthy:
Crowd Counting with Decomposed Uncertainty. AAAI 2020: 11799-11806 - [i7]Min-hwan Oh, Garud Iyengar:
Sequential Anomaly Detection using Inverse Reinforcement Learning. CoRR abs/2004.10398 (2020) - [i6]Min-hwan Oh, Garud Iyengar, Assaf Zeevi:
Sparsity-Agnostic Lasso Bandit. CoRR abs/2007.08477 (2020)
2010 – 2019
- 2019
- [j2]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: 133600-133601 (2019) - [c3]Min-hwan Oh, Garud Iyengar:
Sequential Anomaly Detection using Inverse Reinforcement Learning. KDD 2019: 1480-1490 - [c2]Min-hwan Oh, Garud Iyengar:
Thompson Sampling for Multinomial Logit Contextual Bandits. NeurIPS 2019: 3145-3155 - [i5]Min-hwan Oh, Peder A. Olsen, Karthikeyan Natesan Ramamurthy:
Crowd Counting with Decomposed Uncertainty. CoRR abs/1903.07427 (2019) - [i4]Min-hwan Oh, Peder A. Olsen, Karthikeyan Natesan Ramamurthy:
Counting and Segmenting Sorghum Heads. CoRR abs/1905.13291 (2019) - 2018
- [c1]Hiroki Kanezashi, Toyotaro Suzumura, Dario Garcia-Gasulla, Min-hwan Oh, Satoshi Matsuoka:
Adaptive Pattern Matching with Reinforcement Learning for Dynamic Graphs. HiPC 2018: 92-101 - [i3]Min-hwan Oh, Garud Iyengar:
Directed Exploration in PAC Model-Free Reinforcement Learning. CoRR abs/1808.10552 (2018) - [i2]Hiroki Kanezashi, Toyotaro Suzumura, Dario Garcia-Gasulla, Min-hwan Oh, Satoshi Matsuoka:
Adaptive Pattern Matching with Reinforcement Learning for Dynamic Graphs. CoRR abs/1812.10321 (2018) - 2017
- [i1]Weiyi Liu, Pin-Yu Chen, Hal James Cooper, Min Hwan Oh, Sailung Yeung, Toyotaro Suzumura:
Can GAN Learn Topological Features of a Graph? CoRR abs/1707.06197 (2017) - 2015
- [j1]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)
Coauthor Index
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last updated on 2024-10-07 22:06 CEST by the dblp team
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