| Inertial hegselmann-krause systems B Chazelle, C Wang IEEE Transactions on Automatic Control 62 (8), 3905-3913, 2016 | 53 | 2016 |
| Numerical algorithms to estimate relaxation parameters and Caputo fractional derivative for a fractional thermal wave model in spherical composite medium B Yu, X Jiang, C Wang Applied Mathematics and Computation 274, 106-118, 2016 | 45 | 2016 |
| Noisy Hegselmann-Krause Systems: Phase Transition and the 2R-Conjecture C Wang, Q Li, W E, B Chazelle Journal of Statistical Physics 166, 1209-1225, 2017 | 40 | 2017 |
| Galerkin-Legendre spectral schemes for nonlinear space fractional Schrödinger equation H Zhang, X Jiang, C Wang, W Fan Numerical Algorithms 79, 337-356, 2018 | 38 | 2018 |
| Well-posedness of the limiting equation of a noisy consensus model in opinion dynamics B Chazelle, Q Jiu, Q Li, C Wang Journal of Differential Equations 263 (1), 365-397, 2017 | 29 | 2017 |
| Crank–Nicolson Fourier spectral methods for the space fractional nonlinear Schrödinger equation and its parameter estimation H Zhang, X Jiang, C Wang, S Chen International Journal of Computer Mathematics 96 (2), 238-263, 2019 | 27 | 2019 |
| The knowledge gradient for sequential decision making with stochastic binary feedbacks Y Wang, C Wang, W Powell International Conference on Machine Learning, 2016, 1138-1147, 2016 | 26 | 2016 |
| Discovery of new metastable patterns in diblock copolymers K Jiang, C Wang, Y Huang, P Zhang Communications in Computational Physics 14 (2), 443-460, 2013 | 25 | 2013 |
| Efficient ordered combinatorial semi-bandits for whole-page recommendation Y Wang, H Ouyang, C Wang, J Chen, T Asamov, Y Chang Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 21 | 2017 |
| Functional Frank-Wolfe boosting for general loss functions C Wang, Y Wang, W E, R Schapire arXiv preprint arXiv:1510.02558, 2015 | 14 | 2015 |
| Origin of epitaxies between ordered phases of block copolymers C Wang, K Jiang, P Zhang, AC Shi Soft Matter 7 (22), 10552-10555, 2011 | 12 | 2011 |
| Iterated learning in dynamic social networks B Chazelle, C Wang Journal of Machine Learning Research, 2019 | 9 | 2019 |
| Optimal learning for sequential decision making for expensive cost functions with stochastic binary feedbacks Y Wang, C Wang, W Powell arXiv preprint arXiv:1709.05216, 2017 | 8 | 2017 |
| Computing optimal interfacial structure of modulated phases J Xu, C Wang, AC Shi, P Zhang Communications in Computational Physics 14 (2), 443-460, 2016 | 7 | 2016 |
| Self-sustaining iterated learning B Chazelle, C Wang Innovations in Theoretical Computer Science (2017), 1-17 1, 2016 | 4 | 2016 |
| Gaussian learning-without-recall in a dynamic social network C Wang, B Chazelle 2017 American Control Conference (ACC), 5109-5114, 2017 | 3 | 2017 |
| Thompson Sampling for Contextual Combinatorial Bandits Y Wang, H Ouyang, C Wang, J Chen, T Asamov, Y Chang WOODSTOK’97, 1997 | 3 | 1997 |
| Non-stationary a/b tests: Optimal variance reduction, bias correction, and valid inference Y Wu, Z Zheng, G Zhang, Z Zhang, C Wang Bias Correction, and Valid Inference (May 20, 2022), 2022 | 2 | 2022 |
| Reference product search C Wang, L Tang, S Bian, D Zhang, Z Zhang, Y Wu Companion Proceedings of the 2019 World Wide Web Conference, 404-410, 2019 | 2 | 2019 |
| An Opinion Dynamics Model with Increasing Self-Confidence C Wang arXiv preprint arXiv:1609.05732, 2016 | 2 | 2016 |
Bernard ChazellePrinceton UniversityVerified email at cs.princeton.edu
