Yin, Mingzhang

20 publications

ICLRW 2025 Bayesian Invariance Modeling of Multi-Environment Data Luhuan Wu, Mingzhang Yin, Yixin Wang, John Patrick Cunningham, David Blei
AAAI 2025 Confounding-Robust Deferral Policy Learning Ruijiang Gao, Mingzhang Yin
MLJ 2024 Adjusting Regression Models for Conditional Uncertainty Calibration Ruijiang Gao, Mingzhang Yin, James McInerney, Nathan Kallus
JMLR 2024 Optimization-Based Causal Estimation from Heterogeneous Environments Mingzhang Yin, Yixin Wang, David M. Blei
NeurIPS 2024 SEL-BALD: Deep Bayesian Active Learning with Selective Labels Ruijiang Gao, Mingzhang Yin, Maytal Saar-Tsechansky
ICML 2024 Score Identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation Mingyuan Zhou, Huangjie Zheng, Zhendong Wang, Mingzhang Yin, Hai Huang
AAAI 2023 Gradient Estimation for Binary Latent Variables via Gradient Variance Clipping Russell Z. Kunes, Mingzhang Yin, Max Land, Doron Haviv, Dana Pe'er, Simon Tavaré
NeurIPSW 2023 Nonparametric Discrete Choice Experiments with Machine Learning Guided Adaptive Design Mingzhang Yin, Ruijiang Gao, Weiran Lin, Steven M. Shugan
AISTATS 2023 Probabilistic Conformal Prediction Using Conditional Random Samples Zhendong Wang, Ruijiang Gao, Mingzhang Yin, Mingyuan Zhou, David Blei
NeurIPSW 2022 Generalized Synthetic Control Method with State-Space Model Junzhe Shao, Mingzhang Yin, Xiaoxuan Cai, Linda Valeri
ICMLW 2022 Optimization-Based Causal Estimation from Heterogenous Environments Mingzhang Yin, Yixin Wang, David Blei
CLeaR 2022 Partial Identification with Noisy Covariates: A Robust Optimization Approach Wenshuo Guo, Mingzhang Yin, Yixin Wang, Michael Jordan
AISTATS 2020 A Theoretical Case Study of Structured Variational Inference for Community Detection Mingzhang Yin, Y. X. Rachel Wang, Purnamrita Sarkar
AISTATS 2020 Discrete Action On-Policy Learning with Action-Value Critic Yuguang Yue, Yunhao Tang, Mingzhang Yin, Mingyuan Zhou
ICLR 2020 Meta-Learning Without Memorization Mingzhang Yin, George Tucker, Mingyuan Zhou, Sergey Levine, Chelsea Finn
UAI 2020 Pairwise Supervised Hashing with Bernoulli Variational Auto-Encoder and Self-Control Gradient Estimator Siamak Zamani Dadaneh, Shahin Boluki, Mingzhang Yin, Mingyuan Zhou, Xiaoning Qian
ICLR 2019 ARM: Augment-REINFORCE-Merge Gradient for Stochastic Binary Networks Mingzhang Yin, Mingyuan Zhou
ICML 2019 ARSM: Augment-REINFORCE-Swap-Merge Estimator for Gradient Backpropagation Through Categorical Variables Mingzhang Yin, Yuguang Yue, Mingyuan Zhou
ICML 2018 Semi-Implicit Variational Inference Mingzhang Yin, Mingyuan Zhou
NeurIPS 2017 Convergence of Gradient EM on Multi-Component Mixture of Gaussians Bowei Yan, Mingzhang Yin, Purnamrita Sarkar