Mingzhang Yin

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Mingyuan ZhouAssociate Professor, University of Texas at AustinPreverjeni e-poštni naslov na mccombs.utexas.edu
Yixin WangUniversity of MichiganPreverjeni e-poštni naslov na umich.edu
Purnamrita SarkarAssociate Professor, Statistics and Data Sciences, University of Texas at AustinPreverjeni e-poštni naslov na austin.utexas.edu
Bowei YanUniversity of Texas at AustinPreverjeni e-poštni naslov na utexas.edu
David BleiProfessor of Statistics and Computer Science, Columbia UniversityPreverjeni e-poštni naslov na columbia.edu
Chelsea FinnStanford University, Physical IntelligencePreverjeni e-poštni naslov na cs.stanford.edu
George TuckerGoogle DeepMindPreverjeni e-poštni naslov na google.com
Sergey LevineUC Berkeley, Physical IntelligencePreverjeni e-poštni naslov na eecs.berkeley.edu
Ruijiang GaoUniversity of Texas at DallasPreverjeni e-poštni naslov na utdallas.edu
Xiaoning QianTexas A&M UniversityPreverjeni e-poštni naslov na ece.tamu.edu
Zhendong WangUniversity of Texas at AustinPreverjeni e-poštni naslov na utexas.edu
Yuguang YueAmazonPreverjeni e-poštni naslov na utexas.edu
Claudia ShiPhD Student, Columbia UniversityPreverjeni e-poštni naslov na columbia.edu
Nhat HoProfessor at University of Texas, AustinPreverjeni e-poštni naslov na utexas.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyPreverjeni e-poštni naslov na cs.berkeley.edu
Y. X. Rachel WangSchool of Mathematics and Statistics, University of SydneyPreverjeni e-poštni naslov na sydney.edu.au
Asim AnsariWilliam T. Dillard Professor of Marketing, Columbia UniversityPreverjeni e-poštni naslov na columbia.edu

Spremljaj

Mingzhang Yin

Assistant Professor, University of Florida

Preverjeni e-poštni naslov na ufl.edu - Domača stran

Bayesian Statistics Machine Learning Causal Inference Quantitative Marketing


Naslov Razvrsti po navedbah Razvrsti po letniku Razvrsti po naslovu	Navedeno Navedeno	Leto
Meta-Learning without Memorization M Yin, G Tucker, M Zhou, S Levine, C Finn International Conference on Learning Representations (ICLR), 2020	244	2020
Semi-Implicit Variational Inference M Yin, M Zhou International Conference on Machine Learning (ICML), 2018	178	2018
ARM: Augment-REINFORCE-merge gradient for stochastic binary networks M Yin, M Zhou International Conference on Learning Representations (ICLR), 2019	87*	2019
Convergence of Gradient EM on Multi-component Mixture of Gaussians B Yan, M Yin, P Sarkar Advances in Neural Information Processing Systems (NeurIPS), 2017	72*	2017
Conformal sensitivity analysis for individual treatment effects M Yin, C Shi, Y Wang, DM Blei Journal of the American Statistical Association (JASA), 2022	47	2022
ARSM: Augment-reinforce-swap-merge estimator for gradient backpropagation through categorical variables M Yin, Y Yue, M Zhou International Conference on Machine Learning (ICML), 2019	36	2019
Score identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation M Zhou, H Zheng, Z Wang, M Yin, H Huang International Conference on Machine Learning (ICML), 2024	28	2024
Pairwise supervised hashing with Bernoulli variational auto-encoder and self-control gradient estimator SZ Dadaneh, S Boluki, M Yin, M Zhou, X Qian Uncertainty in Artificial Intelligence (UAI), 2020	27	2020
Probabilistic Conformal Prediction Using Conditional Random Samples Z Wang, R Gao, M Yin, M Zhou, DM Blei Artificial Intelligence and Statistics (AISTATS), 2022	23	2022
Partial identification with noisy covariates: A robust optimization approach W Guo, M Yin, Y Wang, MI Jordan Conference on Causal Learning and Reasoning (CLeaR), 2021	23	2021
Optimization-based Causal Estimation from Heterogenous Environments M Yin, Y Wang, DM Blei Journal of Machine Learning Research (JMLR), 2023	21	2023
A Theoretical Case Study of Structured Variational Inference for Community Detection M Yin, YX Wang, P Sarkar Artificial Intelligence and Statistics (AISTATS), 2020	19	2020
Probabilistic Best Subset Selection via Gradient-Based Optimization M Yin, N Ho, B Yan, X Qian, M Zhou arXiv preprint arXiv:2006.06448, 2020	14*	2020
Discrete Action On-Policy Learning with Action-Value Critic Y Yue, Y Tang, M Yin, M Zhou Artificial Intelligence and Statistics (AISTATS), 2019	9	2019
Confounding-robust Policy Improvement with Human-AI Teams R Gao, M Yin AAAI Conference on Artificial Intelligence (AAAI), 2024	7	2024
Topological data analysis in digital marketing C Lakshminarayan, M Yin Applied Stochastic Models in Business and Industry 36 (6), 1014-1028, 2020	5	2020
Probabilistic Machine Learning: New Frontiers for Modeling Consumers and their Choices R Dew, N Padilla, LE Luo, S Oblander, A Ansari, K Boughanmi, M Braun, ... International Journal of Research in Marketing (IJRM), 2024	4	2024
Semi-Implicit Generative Model M Yin, M Zhou Proceedings of the NeurIPS 2018 Workshop on Bayesian Deep Learning (NeurIPS BDL), 2018	4	2018
Gradient Estimation for Binary Latent Variables via Gradient Variance Clipping RZ Kunes, M Yin, M Land, D Haviv, D Pe'er, S Tavaré AAAI Conference on Artificial Intelligence (AAAI), 2022	3*	2022
Meta-learning customer preference dynamics on digital platforms M Yin, K Boughanmi, A Ansari Available at SSRN, 2024	2	2024

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