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

Sawtooth Factorial Topic Embeddings Guided Gamma Belief Network

Hierarchical topic models such as the gamma belief network (GBN) have de...
06/30/2021 ∙ by Zhibin Duan, et al. ∙ 0 ∙ share

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Probabilistic Margins for Instance Reweighting in Adversarial Training

Reweighting adversarial data during training has been recently shown to ...
06/15/2021 ∙ by Qizhou Wang, et al. ∙ 0 ∙ share

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Bayesian Attention Belief Networks

Attention-based neural networks have achieved state-of-the-art results o...
06/09/2021 ∙ by Shujian Zhang, et al. ∙ 0 ∙ share

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Adversarially Adaptive Normalization for Single Domain Generalization

Single domain generalization aims to learn a model that performs well on...
06/01/2021 ∙ by Xinjie Fan, et al. ∙ 8 ∙ share

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ARMS: Antithetic-REINFORCE-Multi-Sample Gradient for Binary Variables

Estimating the gradients for binary variables is a task that arises freq...
05/28/2021 ∙ by Alek Dimitriev, et al. ∙ 0 ∙ share

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Matching Visual Features to Hierarchical Semantic Topics for Image Paragraph Captioning

Observing a set of images and their corresponding paragraph-captions, a ...
05/10/2021 ∙ by Dandan Guo, et al. ∙ 5 ∙ share

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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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Mingyuan Zhou

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