Min-hwan Oh

According to our database, Min-hwan Oh authored at least 23 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Follow-the-Perturbed-Leader with Fréchet-type Tail Distributions: Optimality in Adversarial Bandits and Best-of-Both-Worlds.

Jongyeong Lee, Junya Honda, Shinji Ito, Min-hwan Oh

CoRR, 2024

Learning Uncertainty-Aware Temporally-Extended Actions.

Joongkyu Lee, Seung Joon Park, Yunhao Tang, Min-hwan Oh

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Mixed-Effects Contextual Bandits.

Kyungbok Lee, Myunghee Cho Paik, Min-hwan Oh, Gi-Soo Kim

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Doubly Perturbed Task Free Continual Learning.

Byung Hyun Lee, Min-hwan Oh, Se Young Chun

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Cascading Contextual Assortment Bandits.

Hyun-Jun Choi, Rajan Udwani, Min-hwan Oh

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Model-based Offline Reinforcement Learning with Count-based Conservatism.

Byeongchan Kim, Min Hwan Oh

Proceedings of the International Conference on Machine Learning, 2023

Combinatorial Neural Bandits.

Taehyun Hwang, Kyuwook Chai, Min Hwan Oh

Proceedings of the International Conference on Machine Learning, 2023

Semi-Parametric Contextual Pricing Algorithm using Cox Proportional Hazards Model.

Young-Geun Choi, Gi-Soo Kim, Yunseo Choi, Wooseong Cho, Myunghee Cho Paik, Min-hwan Oh

Proceedings of the International Conference on Machine Learning, 2023

Squeeze All: Novel Estimator and Self-Normalized Bound for Linear Contextual Bandits.

Wonyoung Kim, Myunghee Cho Paik, Min Hwan Oh

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Model-Based Reinforcement Learning with Multinomial Logistic Function Approximation.

Taehyun Hwang, Min-hwan Oh

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Personalized Federated Learning With Server-Side Information.

Jaehun Song, Min Hwan Oh, Hyung-Sin Kim

IEEE Access, 2022

Stochastic-Expert Variational Autoencoder for Collaborative Filtering.

Yoon-Sik Cho, Min-hwan Oh

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

2021

Sparsity-Agnostic Lasso Bandit.

Min-hwan Oh, Garud Iyengar, Assaf Zeevi

Proceedings of the 38th International Conference on Machine Learning, 2021

Multinomial Logit Contextual Bandits: Provable Optimality and Practicality.

Min-hwan Oh, Garud Iyengar

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Crowd Counting with Decomposed Uncertainty.

Min-hwan Oh, Peder A. Olsen, Karthikeyan Natesan Ramamurthy

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Counting and Segmenting Sorghum Heads.

Min-hwan Oh, Peder A. Olsen, Karthikeyan Natesan Ramamurthy

CoRR, 2019

Corrections to "Learning Graph Topological Features via GAN".

Weiyi Liu, Pin-Yu Chen, Fucai Yu, Toyotaro Suzumura, Guangmin Hu, Hal James Cooper, Min-hwan Oh, Sailung Yeung

IEEE Access, 2019

Thompson Sampling for Multinomial Logit Contextual Bandits.

Min-hwan Oh, Garud Iyengar

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Sequential Anomaly Detection using Inverse Reinforcement Learning.

Min-hwan Oh, Garud Iyengar

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

2018

Directed Exploration in PAC Model-Free Reinforcement Learning.

Min-hwan Oh, Garud Iyengar

CoRR, 2018

Adaptive Pattern Matching with Reinforcement Learning for Dynamic Graphs.

Hiroki Kanezashi, Toyotaro Suzumura, Dario Garcia-Gasulla, Min-hwan Oh, Satoshi Matsuoka

Proceedings of the 25th IEEE International Conference on High Performance Computing, 2018

2017

Can GAN Learn Topological Features of a Graph?

Weiyi Liu, Pin-Yu Chen, Hal James Cooper, Min Hwan Oh, Sailung Yeung, Toyotaro Suzumura

CoRR, 2017

2015

Efficient "Shotgun" Inference of Neural Connectivity from Highly Sub-sampled Activity Data.

Daniel Soudry, Suraj Keshri, Patrick Stinson, Min-hwan Oh, Garud Iyengar, Liam Paninski

PLoS Comput. Biol., 2015