| Crowd counting with decomposed uncertainty M Oh, PA Olsen, KN Ramamurthy Proceedings of the AAAI Conference on Artificial Intelligence 34 (7), 11799 …, 2020 | 121 | 2020 |
| Sequential Anomaly Detection using Inverse Reinforcement Learning M Oh, G Iyengar Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 98 | 2019 |
| Efficient "shotgun" inference of neural connectivity from highly sub-sampled activity data D Soudry, S Keshri, P Stinson, M Oh, G Iyengar, L Paninski PLoS computational biology 11 (10), 2015 | 62 | 2015 |
| Sparsity-Agnostic Lasso Bandit M Oh, G Iyengar, A Zeevi International Conference on Machine Learning, 8271-8280, 2021 | 52 | 2021 |
| Thompson Sampling for Multinomial Logit Contextual Bandits M Oh, G Iyengar Advances in Neural Information Processing Systems, 3145-3155, 2019 | 51 | 2019 |
| Graphical model for basketball match simulation M Oh, S Keshri, G Iyengar Proceddings of the 2015 MIT Sloan Sports Analytics Conference, Boston, MA …, 2015 | 40 | 2015 |
| Learning Graph Topological Features via GAN (vol 7, pg 21834, 2019) W Liu, H Cooper, MH Oh, PY Chen, S Yeung, F Yu, T Suzumura, G Hu IEEE ACCESS 7, 133600-133601, 2019 | 37* | 2019 |
| Multinomial logit contextual bandits: Provable optimality and practicality M Oh, G Iyengar Proceedings of the AAAI conference on artificial intelligence 35 (10), 9205-9213, 2021 | 33* | 2021 |
| A shotgun sampling solution for the common input problem in neural connectivity inference D Soudry, S Keshri, P Stinson, M Oh, G Iyengar, L Paninski arXiv preprint arXiv:1309.3724, 2014 | 26 | 2014 |
| Counting and segmenting sorghum heads M Oh, P Olsen, KN Ramamurthy arXiv preprint arXiv:1905.13291, 2019 | 19 | 2019 |
| Adaptive pattern matching with reinforcement learning for dynamic graphs H Kanezashi, T Suzumura, D Garcia-Gasulla, M Oh, S Matsuoka 2018 IEEE 25th International conference on high performance computing (HIPC …, 2018 | 15 | 2018 |
| Stochastic-expert variational autoencoder for collaborative filtering YS Cho, M Oh Proceedings of the ACM Web Conference 2022, 2482-2490, 2022 | 12 | 2022 |
| Automatic event detection in basketball using hidden Markov models with energy based defensive assignment S Keshri, M Oh, S Zhang, G Iyengar Journal of Quantitative Analysis in Sports 15 (2), 141-153, 2019 | 11 | 2019 |
| Model-based reinforcement learning with multinomial logistic function approximation T Hwang, M Oh Proceedings of the AAAI conference on artificial intelligence 37 (7), 7971-7979, 2023 | 8 | 2023 |
| Directed exploration in PAC model-free reinforcement learning M Oh, G Iyengar International Conference on Machine Learning (ICML) Exploration in …, 2018 | 8 | 2018 |
| Personalized federated learning with server-side information J Song, MH Oh, HS Kim IEEE Access 10, 120245-120255, 2022 | 7 | 2022 |
| Model-based Offline Reinforcement Learning with Count-based Conservatism B Kim, M Oh International Conference on Machine Learning, 16728--16746, 2023 | 5 | 2023 |
| Combinatorial Neural Bandits T Hwang, K Chai, M Oh International Conference on Machine Learning, 14203-14236, 2023 | 4 | 2023 |
| Squeeze All: Novel Estimator and Self-Normalized Bound for Linear Contextual Bandits W Kim, MC Paik, M Oh International Conference on Artificial Intelligence and Statistics, 3098-3124, 2023 | 4 | 2023 |
| Nearly minimax optimal regret for multinomial logistic bandit J Lee, M Oh arXiv preprint arXiv:2405.09831, 2024 | 2 | 2024 |
