Mingzhang Yin - RankMe

36 papers A* 8A 4Journal 21Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Bayesian Invariance Modeling of Multi-Environment Data. CoRR Luhuan Wu, Mingzhang Yin, Yixin Wang, John P. Cunningham, David M. Blei
2025	A*	`conf`	Confounding-Robust Deferral Policy Learning. AAAI Ruijiang Gao, Mingzhang Yin
2025	A*	`conf`	Permutative Preference Alignment from Listwise Ranking of Human Judgments. EMNLP Yang Zhao, Yixin Wang, Mingzhang Yin
2024	J	`jnl`	Adjusting Regression Models for Conditional Uncertainty Calibration. CoRR Ruijiang Gao, Mingzhang Yin, James McInerney, Nathan Kallus
2024	J	`jnl`	Adjusting regression models for conditional uncertainty calibration. Mach. Learn. Ruijiang Gao, Mingzhang Yin, James McInerney, Nathan Kallus
2024	J	`jnl`	Optimization-based Causal Estimation from Heterogeneous Environments. J. Mach. Learn. Res. Mingzhang Yin, Yixin Wang, David M. Blei
2024	J	`jnl`	Ordinal Preference Optimization: Aligning Human Preferences via NDCG. CoRR Yang Zhao, Yixin Wang, Mingzhang Yin
2024	A*	`conf`	SEL-BALD: Deep Bayesian Active Learning with Selective Labels. NeurIPS Ruijiang Gao, Mingzhang Yin, Maytal Saar-Tsechansky
2024	A*	`conf`	Score identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation. ICML Mingyuan Zhou, Huangjie Zheng, Zhendong Wang, Mingzhang Yin, Hai Huang
2024	J	`jnl`	Score identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation. CoRR Mingyuan Zhou, Huangjie Zheng, Zhendong Wang, Mingzhang Yin, Hai Huang
2023	J	`jnl`	Confounding-Robust Policy Improvement with Human-AI Teams. CoRR Ruijiang Gao, Mingzhang Yin
2023	A*	`conf`	Gradient Estimation for Binary Latent Variables via Gradient Variance Clipping. AAAI Russell Z. Kunes, Mingzhang Yin, Max Land, Doron Haviv, Dana Pe'er, Simon Tavaré
2023	J	`jnl`	Nonparametric Discrete Choice Experiments with Machine Learning Guided Adaptive Design. CoRR Mingzhang Yin, Ruijiang Gao, Weiran Lin, Steven M. Shugan
2023	A	`conf`	Probabilistic Conformal Prediction Using Conditional Random Samples. AISTATS Zhendong Wang, Ruijiang Gao, Mingzhang Yin, Mingyuan Zhou, David M. Blei
2022	J	`jnl`	Gradient Estimation for Binary Latent Variables via Gradient Variance Clipping. CoRR Russell Z. Kunes, Mingzhang Yin, Max Land, Doron Haviv, Dana Pe'er, Simon Tavaré
2022	—	`conf`	Partial Identification with Noisy Covariates: A Robust Optimization Approach. CLeaR Wenshuo Guo, Mingzhang Yin, Yixin Wang, Michael I. Jordan
2022	J	`jnl`	Partial Identification with Noisy Covariates: A Robust Optimization Approach. CoRR Wenshuo Guo, Mingzhang Yin, Yixin Wang, Michael I. Jordan
2022	J	`jnl`	Probabilistic Conformal Prediction Using Conditional Random Samples. CoRR Zhendong Wang, Ruijiang Gao, Mingzhang Yin, Mingyuan Zhou, David M. Blei
2021	J	`jnl`	Optimization-based Causal Estimation from Heterogenous Environments. CoRR Mingzhang Yin, Yixin Wang, David M. Blei
2020	A	`conf`	A Theoretical Case Study of Structured Variational Inference for Community Detection. AISTATS Mingzhang Yin, Y. X. Rachel Wang, Purnamrita Sarkar
2020	A	`conf`	Discrete Action On-Policy Learning with Action-Value Critic. AISTATS Yuguang Yue, Yunhao Tang, Mingzhang Yin, Mingyuan Zhou
2020	J	`jnl`	Discrete Action On-Policy Learning with Action-Value Critic. CoRR Yuguang Yue, Yunhao Tang, Mingzhang Yin, Mingyuan Zhou
2020	A*	`conf`	Meta-Learning without Memorization. ICLR Mingzhang Yin, George Tucker, Mingyuan Zhou, Sergey Levine, Chelsea Finn
2020	A	`conf`	Pairwise Supervised Hashing with Bernoulli Variational Auto-Encoder and Self-Control Gradient Estimator. UAI Siamak Zamani Dadaneh, Shahin Boluki, Mingzhang Yin, Mingyuan Zhou, Xiaoning Qian
2020	J	`jnl`	Pairwise Supervised Hashing with Bernoulli Variational Auto-Encoder and Self-Control Gradient Estimator. CoRR Siamak Zamani Dadaneh, Shahin Boluki, Mingzhang Yin, Mingyuan Zhou, Xiaoning Qian
2019	—	`conf`	ARM: Augment-REINFORCE-Merge Gradient for Stochastic Binary Networks. ICLR (Poster) Mingzhang Yin, Mingyuan Zhou
2019	A*	`conf`	ARSM: Augment-REINFORCE-Swap-Merge Estimator for Gradient Backpropagation Through Categorical Variables. ICML Mingzhang Yin, Yuguang Yue, Mingyuan Zhou
2019	J	`jnl`	ARSM: Augment-REINFORCE-Swap-Merge Estimator for Gradient Backpropagation Through Categorical Variables. CoRR Mingzhang Yin, Yuguang Yue, Mingyuan Zhou
2019	J	`jnl`	Augment-Reinforce-Merge Policy Gradient for Binary Stochastic Policy. CoRR Yunhao Tang, Mingzhang Yin, Mingyuan Zhou
2019	J	`jnl`	Meta-Learning without Memorization. CoRR Mingzhang Yin, George Tucker, Mingyuan Zhou, Sergey Levine, Chelsea Finn
2019	J	`jnl`	Semi-Implicit Generative Model. CoRR Mingzhang Yin, Mingyuan Zhou
2018	J	`jnl`	ARM: Augment-REINFORCE-Merge Gradient for Discrete Latent Variable Models. CoRR Mingzhang Yin, Mingyuan Zhou
2018	A*	`conf`	Semi-Implicit Variational Inference. ICML Mingzhang Yin, Mingyuan Zhou
2018	J	`jnl`	Semi-Implicit Variational Inference. CoRR Mingzhang Yin, Mingyuan Zhou
2017	—	`conf`	Convergence of Gradient EM on Multi-component Mixture of Gaussians. NIPS Bowei Yan, Mingzhang Yin, Purnamrita Sarkar
2017	J	`jnl`	Statistical Convergence Analysis of Gradient EM on General Gaussian Mixture Models. CoRR Bowei Yan, Mingzhang Yin, Purnamrita Sarkar