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Mingzhang Yin
Mingzhang Yin
Data Science Institute, Columbia University
Verified email at columbia.edu - Homepage
Title
Cited by
Cited by
Year
Meta-Learning without Memorization
M Yin, G Tucker, M Zhou, S Levine, C Finn
International Conference on Learning Representations (ICLR), 2020
1322020
Semi-Implicit Variational Inference
M Yin, M Zhou
International Conference on Machine Learning (ICML), 2018
932018
ARM: Augment-REINFORCE-merge gradient for stochastic binary networks
M Yin, M Zhou
International Conference on Learning Representations (ICLR), 2019
58*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
45*2017
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
212019
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
142020
Probabilistic Best Subset Selection via Gradient-Based Optimization
M Yin, N Ho, B Yan, X Qian, M Zhou
arXiv preprint arXiv:2006.06448, 2020
8*2020
Conformal sensitivity analysis for individual treatment effects
M Yin, C Shi, Y Wang, DM Blei
Journal of the American Statistical Association (JASA), 2021
62021
A Theoretical Case Study of Structured Variational Inference for Community Detection
M Yin, YX Wang, P Sarkar
Artificial Intelligence and Statistics (AISTATS), 2020
62020
Discrete Action On-Policy Learning with Action-Value Critic
Y Yue, Y Tang, M Yin, M Zhou
Artificial Intelligence and Statistics (AISTATS), 2019
62019
Optimization-based Causal Estimation from Heterogenous Environments
M Yin, Y Wang, DM Blei
arXiv preprint arXiv:2109.11990, 2021
22021
Semi-Implicit Generative Model
M Yin, M Zhou
Proceedings of the NeurIPS 2018 Workshop on Bayesian Deep Learning (NeurIPS BDL), 2018
22018
Partial identification with noisy covariates: A robust optimization approach
W Guo, M Yin, Y Wang, MI Jordan
Conference on Causal Learning and Reasoning (CLeaR), 2022
12022
Probabilistic Conformal Prediction Using Conditional Random Samples
Z Wang, R Gao, M Yin, M Zhou, DM Blei
arXiv preprint arXiv:2206.06584, 2022
2022
Variational methods with dependence structure
M Yin
2020
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Articles 1–15