Min-hwan Oh - RankMe

81 papers A* 32A 1Misc 1Journal 47

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Blessings of Multiple Good Arms in Multi-Objective Linear Bandits. CoRR Heesang Ann, Min-hwan Oh
2026	J	`jnl`	Convergence of Muon with Newton-Schulz. CoRR Gyu-Yeol Kim, Min-hwan Oh
2026	J	`jnl`	Tractable Multinomial Logit Contextual Bandits with Non-Linear Utilities. CoRR Taehyun Hwang, Dahngoon Kim, Min-hwan Oh
2025	A*	`conf`	ADAM Optimization with Adaptive Batch Selection. ICLR Gyu-Yeol Kim, Min-hwan Oh
2025	J	`jnl`	ADAM Optimization with Adaptive Batch Selection. CoRR Gyu-Yeol Kim, Min-hwan Oh
2025	J	`jnl`	AI Should Sense Better, Not Just Scale Bigger: Adaptive Sensing as a Paradigm Shift. CoRR Eunsu Baek, Keondo Park, JeongGil Ko, Min-hwan Oh, Taesik Gong, Hyung-Sin Kim
2025	A*	`conf`	Adversarial Policy Optimization for Offline Preference-based Reinforcement Learning. ICLR Hyungkyu Kang, Min-hwan Oh
2025	J	`jnl`	Adversarial Policy Optimization for Offline Preference-based Reinforcement Learning. CoRR Hyungkyu Kang, Min-hwan Oh
2025	J	`jnl`	Batched Stochastic Matching Bandits. CoRR Jung-Hun Kim, Min-hwan Oh
2025	A*	`conf`	Combinatorial Reinforcement Learning with Preference Feedback. ICML Joongkyu Lee, Min-hwan Oh
2025	J	`jnl`	Combinatorial Reinforcement Learning with Preference Feedback. CoRR Joongkyu Lee, Min-hwan Oh
2025	A*	`conf`	Dynamic Assortment Selection and Pricing with Censored Preference Feedback. ICLR Jung-Hun Kim, Min-hwan Oh
2025	J	`jnl`	Dynamic Assortment Selection and Pricing with Censored Preference Feedback. CoRR Jung-Hun Kim, Min-hwan Oh
2025	A*	`conf`	Experimental Design for Semiparametric Bandits. COLT Seok-Jin Kim, Gi-Soo Kim, Min-hwan Oh
2025	J	`jnl`	Experimental Design for Semiparametric Bandits. CoRR Seok-Jin Kim, Gi-Soo Kim, Min-hwan Oh
2025	J	`jnl`	Exploration via Feature Perturbation in Contextual Bandits. CoRR Seouh-won Yi, Min-hwan Oh
2025	J	`jnl`	Follow-the-Perturbed-Leader for Decoupled Bandits: Best-of-Both-Worlds and Practicality. CoRR Chaiwon Kim, Jongyeong Lee, Min-hwan Oh
2025	A*	`conf`	Improved Online Confidence Bounds for Multinomial Logistic Bandits. ICML Joongkyu Lee, Min-hwan Oh
2025	J	`jnl`	Improved Online Confidence Bounds for Multinomial Logistic Bandits. CoRR Joongkyu Lee, Min-hwan Oh
2025	J	`jnl`	Infrequent Exploration in Linear Bandits. CoRR Harin Lee, Min-hwan Oh
2025	A*	`conf`	Lasso Bandit with Compatibility Condition on Optimal Arm. ICLR Harin Lee, Taehyun Hwang, Min-hwan Oh
2025	A*	`conf`	Linear Bandits with Partially Observable Features. ICML Wonyoung Kim, Sungwoo Park, Garud Iyengar, Assaf Zeevi, Min-hwan Oh
2025	J	`jnl`	Linear Bandits with Partially Observable Features. CoRR Wonyoung Kim, Sungwoo Park, Garud Iyengar, Assaf Zeevi, Min-hwan Oh
2025	A*	`conf`	Minimax Optimal Reinforcement Learning with Quasi-Optimism. ICLR Harin Lee, Min-hwan Oh
2025	J	`jnl`	Minimax Optimal Reinforcement Learning with Quasi-Optimism. CoRR Harin Lee, Min-hwan Oh
2025	A*	`conf`	Optimal and Practical Batched Linear Bandit Algorithm. ICML Sanghoon Yu, Min-hwan Oh
2025	J	`jnl`	Optimal and Practical Batched Linear Bandit Algorithm. CoRR Sanghoon Yu, Min-hwan Oh
2025	J	`jnl`	Oracle-Efficient Combinatorial Semi-Bandits. CoRR Jung-Hun Kim, Milan Vojnovic, Min-hwan Oh
2025	J	`jnl`	Preference-based Reinforcement Learning beyond Pairwise Comparisons: Benefits of Multiple Options. CoRR Joongkyu Lee, Seouh-won Yi, Min-hwan Oh
2025	J	`jnl`	Revisiting Follow-the-Perturbed-Leader with Unbounded Perturbations in Bandit Problems. CoRR Jongyeong Lee, Junya Honda, Shinji Ito, Min-hwan Oh
2025	A*	`conf`	Symmetry-Aware GFlowNets. ICML Hohyun Kim, Seunggeun Lee, Min-hwan Oh
2025	J	`jnl`	Symmetry-Aware GFlowNets. CoRR Hohyun Kim, Seunggeun Lee, Min-hwan Oh
2025	J	`jnl`	Thompson Sampling for Multi-Objective Linear Contextual Bandit. CoRR Somangchan Park, Heesang Ann, Min-hwan Oh
2024	A*	`conf`	Demystifying Linear MDPs and Novel Dynamics Aggregation Framework. ICLR Joongkyu Lee, Min-hwan Oh
2024	J	`jnl`	Demystifying Linear MDPs and Novel Dynamics Aggregation Framework. CoRR Joongkyu Lee, Min-hwan Oh
2024	A*	`conf`	Doubly Perturbed Task Free Continual Learning. AAAI Byung Hyun Lee, Min-hwan Oh, Se Young Chun
2024	A*	`conf`	Follow-the-Perturbed-Leader with Fréchet-type Tail Distributions: Optimality in Adversarial Bandits and Best-of-Both-Worlds. COLT Jongyeong Lee, Junya Honda, Shinji Ito, Min-hwan Oh
2024	J	`jnl`	Follow-the-Perturbed-Leader with Fréchet-type Tail Distributions: Optimality in Adversarial Bandits and Best-of-Both-Worlds. CoRR Jongyeong Lee, Junya Honda, Shinji Ito, Min-hwan Oh
2024	A*	`conf`	Improved Regret of Linear Ensemble Sampling. NeurIPS Harin Lee, Min-hwan Oh
2024	J	`jnl`	Improved Regret of Linear Ensemble Sampling. CoRR Harin Lee, Min-hwan Oh
2024	J	`jnl`	Lasso Bandit with Compatibility Condition on Optimal Arm. CoRR Harin Lee, Taehyun Hwang, Min-hwan Oh
2024	A*	`conf`	Learning Uncertainty-Aware Temporally-Extended Actions. AAAI Joongkyu Lee, Seung Joon Park, Yunhao Tang, Min-hwan Oh
2024	J	`jnl`	Learning Uncertainty-Aware Temporally-Extended Actions. CoRR Joongkyu Lee, Seung Joon Park, Yunhao Tang, Min-hwan Oh
2024	A*	`conf`	Local Anti-Concentration Class: Logarithmic Regret for Greedy Linear Contextual Bandit. NeurIPS Seok-Jin Kim, Min-hwan Oh
2024	J	`jnl`	Local Anti-Concentration Class: Logarithmic Regret for Greedy Linear Contextual Bandit. CoRR Seok-Jin Kim, Min-hwan Oh
2024	J	`jnl`	Magnituder Layers for Implicit Neural Representations in 3D. CoRR Sang Min Kim, Byeongchan Kim, Arijit Sehanobish, Krzysztof Choromanski, Dongseok Shim, Avinava Dubey, Min-hwan Oh
2024	A*	`conf`	Mixed-Effects Contextual Bandits. AAAI Kyungbok Lee, Myunghee Cho Paik, Min-hwan Oh, Gi-Soo Kim
2024	A*	`conf`	Nearly Minimax Optimal Regret for Multinomial Logistic Bandit. NeurIPS Joongkyu Lee, Min-hwan Oh
2024	J	`jnl`	Nearly Minimax Optimal Regret for Multinomial Logistic Bandit. CoRR Joongkyu Lee, Min-hwan Oh
2024	A*	`conf`	Queueing Matching Bandits with Preference Feedback. NeurIPS Jung-Hun Kim, Min-hwan Oh
2024	J	`jnl`	Queueing Matching Bandits with Preference Feedback. CoRR Jung-Hun Kim, Min-hwan Oh
2024	A*	`conf`	Randomized Exploration for Reinforcement Learning with Multinomial Logistic Function Approximation. NeurIPS Wooseong Cho, Taehyun Hwang, Joongkyu Lee, Min-hwan Oh
2024	J	`jnl`	Randomized Exploration for Reinforcement Learning with Multinomial Logistic Function Approximation. CoRR Wooseong Cho, Taehyun Hwang, Joongkyu Lee, Min-hwan Oh
2023	A*	`conf`	Cascading Contextual Assortment Bandits. NeurIPS Hyun-Jun Choi, Rajan Udwani, Min-hwan Oh
2023	A*	`conf`	Combinatorial Neural Bandits. ICML Taehyun Hwang, Kyuwook Chai, Min-hwan Oh
2023	J	`jnl`	Combinatorial Neural Bandits. CoRR Taehyun Hwang, Kyuwook Chai, Min-hwan Oh
2023	J	`jnl`	Doubly Perturbed Task-Free Continual Learning. CoRR Byung Hyun Lee, Min-hwan Oh, Se Young Chun
2023	A*	`conf`	Model-Based Reinforcement Learning with Multinomial Logistic Function Approximation. AAAI Taehyun Hwang, Min-hwan Oh
2023	A*	`conf`	Model-based Offline Reinforcement Learning with Count-based Conservatism. ICML Byeongchan Kim, Min-hwan Oh
2023	J	`jnl`	Model-based Offline Reinforcement Learning with Count-based Conservatism. CoRR Byeongchan Kim, Min-hwan Oh
2023	A*	`conf`	Semi-Parametric Contextual Pricing Algorithm using Cox Proportional Hazards Model. ICML Young-Geun Choi, Gi-Soo Kim, Yunseo Choi, Wooseong Cho, Myunghee Cho Paik, Min-hwan Oh
2023	A	`conf`	Squeeze All: Novel Estimator and Self-Normalized Bound for Linear Contextual Bandits. AISTATS Wonyoung Kim, Myunghee Cho Paik, Min-hwan Oh
2022	J	`jnl`	Model-Based Reinforcement Learning with Multinomial Logistic Function Approximation. CoRR Taehyun Hwang, Min-hwan Oh
2022	J	`jnl`	Personalized Federated Learning with Server-Side Information. CoRR Jaehun Song, Min-hwan Oh, Hyung-Sin Kim
2022	J	`jnl`	Squeeze All: Novel Estimator and Self-Normalized Bound for Linear Contextual Bandits. CoRR Wonyoung Kim, Min-hwan Oh, Myunghee Cho Paik
2022	A*	`conf`	Stochastic-Expert Variational Autoencoder for Collaborative Filtering. WWW Yoon-Sik Cho, Min-hwan Oh
2021	A*	`conf`	Multinomial Logit Contextual Bandits: Provable Optimality and Practicality. AAAI Min-hwan Oh, Garud Iyengar
2021	J	`jnl`	Multinomial Logit Contextual Bandits: Provable Optimality and Practicality. CoRR Min-hwan Oh, Garud Iyengar
2021	A*	`conf`	Sparsity-Agnostic Lasso Bandit. ICML Min-hwan Oh, Garud Iyengar, Assaf Zeevi
2020	A*	`conf`	Crowd Counting with Decomposed Uncertainty. AAAI Min-hwan Oh, Peder A. Olsen, Karthikeyan Natesan Ramamurthy
2020	J	`jnl`	Sequential Anomaly Detection using Inverse Reinforcement Learning. CoRR Min-hwan Oh, Garud Iyengar
2020	J	`jnl`	Sparsity-Agnostic Lasso Bandit. CoRR Min-hwan Oh, Garud Iyengar, Assaf Zeevi
2019	J	`jnl`	Corrections to "Learning Graph Topological Features via GAN". IEEE Access Weiyi Liu, Pin-Yu Chen, Fucai Yu, Toyotaro Suzumura, Guangmin Hu, Hal James Cooper, Min-hwan Oh, Sailung Yeung
2019	J	`jnl`	Counting and Segmenting Sorghum Heads. CoRR Min-hwan Oh, Peder A. Olsen, Karthikeyan Natesan Ramamurthy
2019	J	`jnl`	Crowd Counting with Decomposed Uncertainty. CoRR Min-hwan Oh, Peder A. Olsen, Karthikeyan Natesan Ramamurthy
2019	A*	`conf`	Sequential Anomaly Detection using Inverse Reinforcement Learning. KDD Min-hwan Oh, Garud Iyengar
2019	A*	`conf`	Thompson Sampling for Multinomial Logit Contextual Bandits. NeurIPS Min-hwan Oh, Garud Iyengar
2018	Misc	`conf`	Adaptive Pattern Matching with Reinforcement Learning for Dynamic Graphs. HiPC Hiroki Kanezashi, Toyotaro Suzumura, Dario Garcia-Gasulla, Min-hwan Oh, Satoshi Matsuoka
2018	J	`jnl`	Adaptive Pattern Matching with Reinforcement Learning for Dynamic Graphs. CoRR Hiroki Kanezashi, Toyotaro Suzumura, Dario Garcia-Gasulla, Min-hwan Oh, Satoshi Matsuoka
2018	J	`jnl`	Directed Exploration in PAC Model-Free Reinforcement Learning. CoRR Min-hwan Oh, Garud Iyengar
2015	J	`jnl`	Efficient "Shotgun" Inference of Neural Connectivity from Highly Sub-sampled Activity Data. PLoS Comput. Biol. Daniel Soudry, Suraj Keshri, Patrick Stinson, Min-hwan Oh, Garud Iyengar, Liam Paninski