Neural Logic Machines H Dong, J Mao, T Lin, C Wang, L Li, D Zhou arXiv preprint arXiv:1904.11694, 2019 | 273 | 2019 |
Neural Logic Machines H Dong, J Mao, T Lin, C Wang, LL Li, D Zhou International Conference on Learning Representations, 2019 | 273 | 2019 |
Robust influence maximization W Chen, T Lin, Z Tan, M Zhao, X Zhou Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge …, 2016 | 228 | 2016 |
Combinatorial pure exploration of multi-armed bandits S Chen, T Lin, I King, MR Lyu, W Chen Advances in neural information processing systems 27, 2014 | 228 | 2014 |
Real-time Topic-aware Influence Maximization Using Preprocessing W Chen, T Lin, C Yang Computational Social Networks 3 (1), 8, 2016 | 91 | 2016 |
Combinatorial Partial Monitoring Game with Linear Feedback and Its Applications T Lin, B Abrahao, R Kleinberg, JCS Lui, W Chen Proceedings of the 31st International Conference on Machine Learning 32 (1 …, 2014 | 61 | 2014 |
Stochastic online greedy learning with semi-bandit feedbacks T Lin, J Li, W Chen Advances in Neural Information Processing Systems 28, 2015 | 38 | 2015 |
Combining traditional marketing and viral marketing with amphibious influence maximization W Chen, F Li, T Lin, A Rubinstein Proceedings of the Sixteenth ACM Conference on Economics and Computation …, 2015 | 33 | 2015 |
Adaptive mixture of low-rank factorizations for compact neural modeling T Chen, J Lin, T Lin, S Han, C Wang, D Zhou NeurIPS'19: Energy Efficient Machine Learning and Cognitive Computing (EMC …, 2018 | 22 | 2018 |
Doubly Sparse: Sparse Mixture of Sparse Experts for Efficient Softmax Inference S Liao, T Chen, T Lin, D Zhou, C Wang arXiv preprint arXiv:1901.10668, 2019 | | 2019 |
On the Combinatorial Pure Exploration of Multi-Armed Bandit Z Tan, T Lin, J Li, W Chen | | |