Mingyuan Zhou

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Duke University ∙ The University of Texas at Austin ∙ Microsoft ∙ University of Delaware

Assistant Professor of Statistics at The University of Texas at Austin

Partition-Guided GANs

Despite the success of Generative Adversarial Networks (GANs), their tra...
04/02/2021 ∙ by Mohammadreza Armandpour, et al. ∙ 0 ∙ share

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Contextual Dropout: An Efficient Sample-Dependent Dropout Module

Dropout has been demonstrated as a simple and effective module to not on...
03/06/2021 ∙ by Xinjie Fan, et al. ∙ 28 ∙ share

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Comparing Probability Distributions with Conditional Transport

To measure the difference between two probability distributions, we prop...
12/28/2020 ∙ by Huangjie Zheng, et al. ∙ 6 ∙ share

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Self-supervised Pre-training with Hard Examples Improves Visual Representations

Self-supervised pre-training (SSP) employs random image transformations ...
12/25/2020 ∙ by Chunyuan Li, et al. ∙ 0 ∙ share

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Hyperbolic Graph Embedding with Enhanced Semi-Implicit Variational Inference

Efficient modeling of relational data arising in physical, social, and i...
10/31/2020 ∙ by Ali Lotfi Rezaabad, et al. ∙ 0 ∙ share

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Convex Polytope Trees

A decision tree is commonly restricted to use a single hyperplane to spl...
10/21/2020 ∙ by Mohammadreza Armandpour, et al. ∙ 0 ∙ share

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Bayesian Attention Modules

Attention modules, as simple and effective tools, have not only enabled ...
10/20/2020 ∙ by Xinjie Fan, et al. ∙ 0 ∙ share

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MCMC-Interactive Variational Inference

Leveraging well-established MCMC strategies, we propose MCMC-interactive...
10/02/2020 ∙ by Quan Zhang, et al. ∙ 0 ∙ share

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Variational Temporal Deep Generative Model for Radar HRRP Target Recognition

We develop a recurrent gamma belief network (rGBN) for radar automatic t...
09/28/2020 ∙ by Dandan Guo, et al. ∙ 3 ∙ share

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Graph Gamma Process Generalized Linear Dynamical Systems

We introduce graph gamma process (GGP) linear dynamical systems to model...
07/25/2020 ∙ by Rahi Kalantari, et al. ∙ 0 ∙ share

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Implicit Distributional Reinforcement Learning

To improve the sample efficiency of policy-gradient based reinforcement ...
07/13/2020 ∙ by Yuguang Yue, et al. ∙ 23 ∙ share

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Probabilistic Best Subset Selection via Gradient-Based Optimization

In high-dimensional statistics, variable selection is an optimization pr...
06/11/2020 ∙ by Mingzhang Yin, et al. ∙ 0 ∙ share

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Probabilistic Best Subset Selection by Gradient-Based Optimization

In high-dimensional statistics, variable selection is an optimization pr...
06/11/2020 ∙ by Mingzhang Yin, et al. ∙ 0 ∙ share

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Bayesian Graph Neural Networks with Adaptive Connection Sampling

We propose a unified framework for adaptive connection sampling in graph...
06/07/2020 ∙ by Arman Hasanzadeh, et al. ∙ 19 ∙ share

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Pairwise Supervised Hashing with Bernoulli Variational Auto-Encoder and Self-Control Gradient Estimator

Semantic hashing has become a crucial component of fast similarity searc...
05/21/2020 ∙ by Siamak Zamani Dadaneh, et al. ∙ 11 ∙ share

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Mutual Information Gradient Estimation for Representation Learning

Mutual Information (MI) plays an important role in representation learni...
05/03/2020 ∙ by Liangjian Wen, et al. ∙ 6 ∙ share

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Learnable Bernoulli Dropout for Bayesian Deep Learning

In this work, we propose learnable Bernoulli dropout (LBD), a new model-...
02/12/2020 ∙ by Shahin Boluki, et al. ∙ 0 ∙ share

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Adaptive Correlated Monte Carlo for Contextual Categorical Sequence Generation

Sequence generation models are commonly refined with reinforcement learn...
12/31/2019 ∙ by Xinjie Fan, et al. ∙ 21 ∙ share

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Recurrent Hierarchical Topic-Guided Neural Language Models

To simultaneously capture syntax and global semantics from a text corpus...
12/21/2019 ∙ by Dandan Guo, et al. ∙ 0 ∙ share

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Meta-Learning without Memorization

The ability to learn new concepts with small amounts of data is a critic...
12/09/2019 ∙ by Mingzhang Yin, et al. ∙ 19 ∙ share

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Weibull Racing Time-to-event Modeling and Analysis of Online Borrowers' Loan Payoff and Default

We propose Weibull delegate racing (WDR) to explicitly model surviving u...
11/02/2019 ∙ by Quan Zhang, et al. ∙ 0 ∙ share

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ARSM Gradient Estimator for Supervised Learning to Rank

We propose a new model for supervised learning to rank. In our model, th...
11/01/2019 ∙ by Siamak Zamani Dadaneh, et al. ∙ 0 ∙ share

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Thompson Sampling via Local Uncertainty

Thompson sampling is an efficient algorithm for sequential decision maki...
10/30/2019 ∙ by Zhendong Wang, et al. ∙ 0 ∙ share

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Poisson-Randomized Gamma Dynamical Systems

This paper presents the Poisson-randomized gamma dynamical system (PRGDS...
10/28/2019 ∙ by Aaron Schein, et al. ∙ 34 ∙ share

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Semi-Implicit Stochastic Recurrent Neural Networks

Stochastic recurrent neural networks with latent random variables of com...
10/28/2019 ∙ by Ehsan Hajiramezanali, et al. ∙ 0 ∙ share

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Semi-supervised Learning using Adversarial Training with Good and Bad Samples

In this work, we investigate semi-supervised learning (SSL) for image cl...
10/18/2019 ∙ by Wenyuan Li, et al. ∙ 20 ∙ share

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Variational Graph Recurrent Neural Networks

Representation learning over graph structured data has been mostly studi...
08/26/2019 ∙ by Ehsan Hajiramezanali, et al. ∙ 0 ∙ share

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Semi-Implicit Graph Variational Auto-Encoders

Semi-implicit graph variational auto-encoder (SIG-VAE) is proposed to ex...
08/19/2019 ∙ by Arman Hasanzadeh, et al. ∙ 0 ∙ share

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Bayesian Gamma-Negative Binomial Modeling of Single-Cell RNA Sequencing Data

Background: Single-cell RNA sequencing (scRNA-seq) is a powerful profili...
08/01/2019 ∙ by Siamak Zamani Dadaneh, et al. ∙ 0 ∙ share

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Semi-Implicit Generative Model

To combine explicit and implicit generative models, we introduce semi-im...
05/29/2019 ∙ by Mingzhang Yin, et al. ∙ 0 ∙ share

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Variational Hetero-Encoder Randomized Generative Adversarial Networks for Joint Image-Text Modeling

For bidirectional joint image-text modeling, we develop variational hete...
05/18/2019 ∙ by Hao Zhang, et al. ∙ 4 ∙ share

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Convolutional Poisson Gamma Belief Network

For text analysis, one often resorts to a lossy representation that eith...
05/14/2019 ∙ by Chaojie Wang, et al. ∙ 0 ∙ share

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ARSM: Augment-REINFORCE-Swap-Merge Estimator for Gradient Backpropagation Through Categorical Variables

To address the challenge of backpropagating the gradient through categor...
05/04/2019 ∙ by Mingzhang Yin, et al. ∙ 0 ∙ share

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Deep Generative Models for Sparse, High-dimensional, and Overdispersed Discrete Data

Many applications, such as text modelling, high-throughput sequencing, a...
05/02/2019 ∙ by He Zhao, et al. ∙ 0 ∙ share

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Non-Lambertian Surface Shape and Reflectance Reconstruction Using Concentric Multi-Spectral Light Field

Recovering the shape and reflectance of non-Lambertian surfaces remains ...
04/09/2019 ∙ by Mingyuan Zhou, et al. ∙ 0 ∙ share

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3D Face Reconstruction Using Color Photometric Stereo with Uncalibrated Near Point Lights

We present a new color photometric stereo (CPS) method that can recover ...
04/04/2019 ∙ by Zhang Chen, et al. ∙ 0 ∙ share

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Augment-Reinforce-Merge Policy Gradient for Binary Stochastic Policy

Due to the high variance of policy gradients, on-policy optimization alg...
03/13/2019 ∙ by Yunhao Tang, et al. ∙ 5 ∙ share

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Dirichlet belief networks for topic structure learning

Recently, considerable research effort has been devoted to developing de...
11/02/2018 ∙ by He Zhao, et al. ∙ 0 ∙ share

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Deep Poisson gamma dynamical systems

We develop deep Poisson-gamma dynamical systems (DPGDS) to model sequent...
10/26/2018 ∙ by Dandan Guo, et al. ∙ 0 ∙ share

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Bayesian multi-domain learning for cancer subtype discovery from next-generation sequencing count data

Precision medicine aims for personalized prognosis and therapeutics by u...
10/22/2018 ∙ by Ehsan Hajiramezanali, et al. ∙ 0 ∙ share

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Nonparametric Bayesian Lomax delegate racing for survival analysis with competing risks

We propose Lomax delegate racing (LDR) to explicitly model the mechanism...
10/19/2018 ∙ by Quan Zhang, et al. ∙ 0 ∙ share

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ARM: Augment-REINFORCE-Merge Gradient for Discrete Latent Variable Models

To backpropagate the gradients through discrete stochastic layers, we en...
07/30/2018 ∙ by Mingzhang Yin, et al. ∙ 0 ∙ share

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Semi-Implicit Variational Inference

Semi-implicit variational inference (SIVI) is introduced to expand the c...
05/28/2018 ∙ by Mingzhang Yin, et al. ∙ 0 ∙ share

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Parsimonious Bayesian deep networks

Combining Bayesian nonparametrics and a forward model selection strategy...
05/22/2018 ∙ by Mingyuan Zhou, et al. ∙ 0 ∙ share

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Masking: A New Perspective of Noisy Supervision

It is important to learn classifiers under noisy labels due to their ubi...
05/21/2018 ∙ by Bo Han, et al. ∙ 0 ∙ share

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Locally Private Bayesian Inference for Count Models

As more aspects of social interaction are digitally recorded, there is a...
03/22/2018 ∙ by Aaron Schein, et al. ∙ 0 ∙ share

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Differential Expression Analysis of Dynamical Sequencing Count Data with a Gamma Markov Chain

Next-generation sequencing (NGS) to profile temporal changes in living s...
03/07/2018 ∙ by Ehsan Hajiramezanali, et al. ∙ 0 ∙ share

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WHAI: Weibull Hybrid Autoencoding Inference for Deep Topic Modeling

To train an inference network jointly with a deep generative topic model...
03/04/2018 ∙ by Hao Zhang, et al. ∙ 0 ∙ share

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Discussion on "Sparse graphs using exchangeable random measures" by Francois Caron and Emily B. Fox

This is a discussion on "Sparse graphs using exchangeable random measure...
02/21/2018 ∙ by Mingyuan Zhou, et al. ∙ 0 ∙ share

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Nonparametric Bayesian Sparse Graph Linear Dynamical Systems

A nonparametric Bayesian sparse graph linear dynamical system (SGLDS) is...
02/21/2018 ∙ by Rahi Kalantari, et al. ∙ 0 ∙ share

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Mingyuan Zhou

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