| Combating noisy labels by agreement: A joint training method with co-regularization H Wei, L Feng, X Chen, B An Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 623 | 2020 |
| Protect: A deployed game theoretic system to protect the ports of the united states E Shieh, B An, R Yang, M Tambe, C Baldwin, J DiRenzo, B Maule, ... Proceedings of the 11th international conference on autonomous agents and …, 2012 | 357 | 2012 |
| Optimal electric vehicle fast charging station placement based on game theoretical framework Y Xiong, J Gan, B An, C Miao, ALC Bazzan IEEE Transactions on Intelligent Transportation Systems 19 (8), 2493-2504, 2017 | 298 | 2017 |
| Automated negotiation with decommitment for dynamic resource allocation in cloud computing B An, V Lesser, D Irwin, M Zink Proceedings of the 9th International Conference on Autonomous Agents and …, 2010 | 276 | 2010 |
| Mitigating neural network overconfidence with logit normalization H Wei, R Xie, H Cheng, L Feng, B An, Y Li International conference on machine learning, 23631-23644, 2022 | 272 | 2022 |
| Poi2vec: Geographical latent representation for predicting future visitors S Feng, G Cong, B An, YM Chee Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 272 | 2017 |
| Stackelberg security games: Looking beyond a decade of success A Sinha, F Fang, B An, C Kiekintveld, M Tambe IJCAI, 2018 | 233 | 2018 |
| Deploying paws: Field optimization of the protection assistant for wildlife security F Fang, T Nguyen, R Pickles, W Lam, G Clements, B An, A Singh, ... Proceedings of the AAAI Conference on Artificial Intelligence 30 (2), 3966-3973, 2016 | 181 | 2016 |
| Can cross entropy loss be robust to label noise? L Feng, S Shu, Z Lin, F Lv, L Li, B An Proceedings of the twenty-ninth international conference on international …, 2021 | 176 | 2021 |
| Provably consistent partial-label learning L Feng, J Lv, B Han, M Xu, G Niu, X Geng, B An, M Sugiyama Advances in neural information processing systems 33, 10948-10960, 2020 | 163 | 2020 |
| Partial label learning with self-guided retraining L Feng, B An Proceedings of the AAAI conference on artificial intelligence 33 (01), 3542-3549, 2019 | 139 | 2019 |
| Learning efficient multi-agent communication: An information bottleneck approach R Wang, X He, R Yu, W Qiu, B An, Z Rabinovich International Conference on Machine Learning, 9908-9918, 2020 | 111 | 2020 |
| Learning with multiple complementary labels L Feng, T Kaneko, B Han, G Niu, B An, M Sugiyama International conference on machine learning, 3072-3081, 2020 | 108 | 2020 |
| Leveraging Latent Label Distributions for Partial Label Learning. L Feng, B An IJCAI, 2107-2113, 2018 | 107 | 2018 |
| Toward efficient team formation for crowdsourcing in noncooperative social networks W Wang, J Jiang, B An, Y Jiang, B Chen IEEE transactions on cybernetics 47 (12), 4208-4222, 2016 | 97 | 2016 |
| Strategic agents for multi-resource negotiation B An, V Lesser, KM Sim Autonomous Agents and Multi-Agent Systems 23, 114-153, 2011 | 95 | 2011 |
| Guards and protect: Next generation applications of security games B An, J Pita, E Shieh, M Tambe, C Kiekintveld, J Marecki ACM SIGecom Exchanges 10 (1), 31-34, 2011 | 89 | 2011 |
| A deployed quantal response-based patrol planning system for the US Coast Guard B An, F Ordóñez, M Tambe, E Shieh, R Yang, C Baldwin, J DiRenzo III, ... Interfaces 43 (5), 400-420, 2013 | 88 | 2013 |
| Efficient label contamination attacks against black-box learning models. M Zhao, B An, W Gao, T Zhang IJCAI, 3945-3951, 2017 | 84 | 2017 |
| Open-set label noise can improve robustness against inherent label noise H Wei, L Tao, R Xie, B An Advances in Neural Information Processing Systems 34, 7978-7992, 2021 | 83 | 2021 |
Milind TambeProfessor & Director CRCS Center @Harvard; Director "AI for Social Good" @Google ResearchBestätigte E-Mail-Adresse bei harvard.edu