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2020 – today
- 2024
[j2]Mingzhang Yin, Yixin Wang, David M. Blei:
Optimization-based Causal Estimation from Heterogeneous Environments. J. Mach. Learn. Res. 25: 168:1-168:44 (2024)- [j1]Ruijiang Gao, Mingzhang Yin, James McInerney, Nathan Kallus:
Adjusting regression models for conditional uncertainty calibration. Mach. Learn. 113(11): 8347-8370 (2024) - [c12]Mingyuan Zhou, Huangjie Zheng, Zhendong Wang, Mingzhang Yin, Hai Huang:
Score identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation. ICML 2024 - [i18]Mingyuan Zhou, Huangjie Zheng, Zhendong Wang, Mingzhang Yin, Hai Huang:
Score identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation. CoRR abs/2404.04057 (2024) - [i17]Ruijiang Gao, Mingzhang Yin, James McInerney, Nathan Kallus:
Adjusting Regression Models for Conditional Uncertainty Calibration. CoRR abs/2409.17466 (2024) - [i16]Yang Zhao, Yixin Wang, Mingzhang Yin:
Ordinal Preference Optimization: Aligning Human Preferences via NDCG. CoRR abs/2410.04346 (2024) - 2023
- [c11]Russell Z. Kunes, Mingzhang Yin, Max Land, Doron Haviv, Dana Pe'er, Simon Tavaré:
Gradient Estimation for Binary Latent Variables via Gradient Variance Clipping. AAAI 2023: 8405-8412 - [c10]Zhendong Wang, Ruijiang Gao, Mingzhang Yin, Mingyuan Zhou, David M. Blei:
Probabilistic Conformal Prediction Using Conditional Random Samples. AISTATS 2023: 8814-8836 - [i15]Ruijiang Gao, Mingzhang Yin:
Confounding-Robust Policy Improvement with Human-AI Teams. CoRR abs/2310.08824 (2023) - [i14]Mingzhang Yin, Ruijiang Gao, Weiran Lin, Steven M. Shugan:
Nonparametric Discrete Choice Experiments with Machine Learning Guided Adaptive Design. CoRR abs/2310.12026 (2023) - 2022
- [c9]Wenshuo Guo, Mingzhang Yin, Yixin Wang, Michael I. Jordan:
Partial Identification with Noisy Covariates: A Robust Optimization Approach. CLeaR 2022: 318-335 - [i13]Wenshuo Guo, Mingzhang Yin, Yixin Wang, Michael I. Jordan:
Partial Identification with Noisy Covariates: A Robust Optimization Approach. CoRR abs/2202.10665 (2022) - [i12]Zhendong Wang, Ruijiang Gao, Mingzhang Yin, Mingyuan Zhou, David M. Blei:
Probabilistic Conformal Prediction Using Conditional Random Samples. CoRR abs/2206.06584 (2022) - [i11]Russell Z. Kunes, Mingzhang Yin, Max Land, Doron Haviv, Dana Pe'er, Simon Tavaré:
Gradient Estimation for Binary Latent Variables via Gradient Variance Clipping. CoRR abs/2208.06124 (2022) - 2021
- [i10]Mingzhang Yin, Yixin Wang, David M. Blei:
Optimization-based Causal Estimation from Heterogenous Environments. CoRR abs/2109.11990 (2021) - 2020
- [c8]Yuguang Yue, Yunhao Tang, Mingzhang Yin, Mingyuan Zhou
:
Discrete Action On-Policy Learning with Action-Value Critic. AISTATS 2020: 1977-1987 - [c7]Mingzhang Yin, Y. X. Rachel Wang, Purnamrita Sarkar:
A Theoretical Case Study of Structured Variational Inference for Community Detection. AISTATS 2020: 3750-3761 - [c6]Mingzhang Yin, George Tucker, Mingyuan Zhou, Sergey Levine, Chelsea Finn:
Meta-Learning without Memorization. ICLR 2020 - [c5]Siamak Zamani Dadaneh, Shahin Boluki, Mingzhang Yin, Mingyuan Zhou, Xiaoning Qian:
Pairwise Supervised Hashing with Bernoulli Variational Auto-Encoder and Self-Control Gradient Estimator. UAI 2020: 540-549 - [i9]Yuguang Yue, Yunhao Tang, Mingzhang Yin, Mingyuan Yin:
Discrete Action On-Policy Learning with Action-Value Critic. CoRR abs/2002.03534 (2020) - [i8]Siamak Zamani Dadaneh, Shahin Boluki, Mingzhang Yin, Mingyuan Zhou, Xiaoning Qian:
Pairwise Supervised Hashing with Bernoulli Variational Auto-Encoder and Self-Control Gradient Estimator. CoRR abs/2005.10477 (2020)
2010 – 2019
- 2019
- [c4]Mingzhang Yin, Mingyuan Zhou:
ARM: Augment-REINFORCE-Merge Gradient for Stochastic Binary Networks. ICLR (Poster) 2019 - [c3]Mingzhang Yin, Yuguang Yue, Mingyuan Zhou:
ARSM: Augment-REINFORCE-Swap-Merge Estimator for Gradient Backpropagation Through Categorical Variables. ICML 2019: 7095-7104 - [i7]Yunhao Tang, Mingzhang Yin, Mingyuan Zhou:
Augment-Reinforce-Merge Policy Gradient for Binary Stochastic Policy. CoRR abs/1903.05284 (2019) - [i6]Mingzhang Yin, Yuguang Yue, Mingyuan Zhou:
ARSM: Augment-REINFORCE-Swap-Merge Estimator for Gradient Backpropagation Through Categorical Variables. CoRR abs/1905.01413 (2019) - [i5]Mingzhang Yin, Mingyuan Zhou:
Semi-Implicit Generative Model. CoRR abs/1905.12659 (2019) - [i4]Mingzhang Yin, George Tucker, Mingyuan Zhou, Sergey Levine, Chelsea Finn:
Meta-Learning without Memorization. CoRR abs/1912.03820 (2019) - 2018
- [c2]Mingzhang Yin, Mingyuan Zhou:
Semi-Implicit Variational Inference. ICML 2018: 5646-5655 - [i3]Mingzhang Yin, Mingyuan Zhou:
Semi-Implicit Variational Inference. CoRR abs/1805.11183 (2018) - [i2]Mingzhang Yin, Mingyuan Zhou:
ARM: Augment-REINFORCE-Merge Gradient for Discrete Latent Variable Models. CoRR abs/1807.11143 (2018) - 2017
- [c1]Bowei Yan, Mingzhang Yin, Purnamrita Sarkar:
Convergence of Gradient EM on Multi-component Mixture of Gaussians. NIPS 2017: 6956-6966 - [i1]Bowei Yan, Mingzhang Yin, Purnamrita Sarkar:
Statistical Convergence Analysis of Gradient EM on General Gaussian Mixture Models. CoRR abs/1705.08530 (2017)
Coauthor Index
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