- Supplement to Tree-Structured Infinite Sparse Factor XianXing Zhang
- Tree-Structured Infinite Sparse Factor Model XianXing Zhang XIANXING.ZHANG@DUKE.EDU
- Classification with Incomplete Data Using Dirichlet Process Priors
- Hierarchical Bayesian Modeling of Topics in Time-Stamped Documents
- Exploiting Structure in Wavelet-Based Bayesian Compressive Sensing
- Variational Inference for Stick-Breaking Beta Process Priors John Paisley1
- Bayesian Robust Principal Component Analysis Xinghao Ding, 1
- Logistic Stick-Breaking Process Lu Ren lr@ece.duke.edu
- Coherence, Compressive Sensing and Random Sensor Arrays Lawrence Carin, Dehong Liu and Bin Guo
- Dictionary Learning for Noisy and Incomplete Hyperspectral Images 1Zhengming Xing, 1Mingyuan Zhou, 2Alexey Castrodad, 2Guillermo Sapiro and 1Lawrence Carin
- Hierarchical Bayesian Embeddings for Analysis and Synthesis of Dynamic Data
- Predicting Viral Infection from High-Dimensional Biomarker Trajectories 1Minhua Chen, 2Aimee Zaas, 2Christopher Woods, 2Geoffrey S. Ginsburg,
- Nonparametric Bayesian Matrix Completion Mingyuan Zhou, Chunping Wang, Minhua Chen, John Paisley, 1David Dunson and Lawrence Carin
- A Stick-Breaking Construction of the Beta Process John Paisley1
- Bayesian Inference of the Number of Factors in Gene-Expression Analysis: Application to Human Virus Challenge Studies
- Tree-Structured Compressive Sensing with Variational Bayesian Analysis Lihan He, Haojun Chen and Lawrence Carin
- Dynamic Nonparametric Bayesian Models for Analysis of Music
- Hidden Markov Models with Stick Breaking Priors John Paisley and Lawrence Carin
- Journal of Machine Learning Research Submitted 01/2009 Multi-task Reinforcement Learning in Partially Observable
- Detection of Viruses via Statistical Gene-Expression Analysis
- On the Relationship Between Compressive Sensing and Random Sensor Arrays Lawrence Carin
- The Infinite Regionalized Policy Representation Miao Liu, Xuejun Liao, Lawrence Carin miao.liu,xjliao,lcarin@duke.edu
- Joint Analysis of Time-Evolving Binary Matrices and Associated Documents
- Compressive Sensing on Manifolds Using a Nonparametric Mixture of Factor Analyzers: Algorithm and Performance Bounds
- On the Integration of Topic Modeling and Dictionary Learning Lingbo Li ll83@duke.edu
- Deep Learning with Hierarchical Convolutional Factor Analysis Guillermo Sapiro, 3
- Sticky Hidden Markov Modeling of Comparative Genomic Hybridization Minhua Chen, 2
- Active Learning and Basis Selection for Kernel-Based Linear Models: A Bayesian Perspective
- Nonparametric Factor Analysis with Beta Process Priors John Paisley jwp4@ee.duke.edu
- Semi-Supervised Multitask Learning Qiuhua Liu, 1
- The Hierarchical Beta Process for Convolutional Factor Analysis and Deep Learning
- Supplement to Hierarchical Topic Modeling for Analysis of Time-Evolving Personal Choices
- Nonparametric Bayesian Segmentation of Multivariate Inhomogeneous Space-Time Poisson Process
- Bayesian Learning of Sparse Gaussian Graphical Models Minhua Chen, 2
- Analysis of Space-Time Relational Data with Application to Legislative Voting
- Hierarchical Topic Modeling for Analysis of Time-Evolving Personal Choices
- Dictionary Learning for Noisy and Incomplete Hyperspectral Images 1Zhengming Xing, 1Mingyuan Zhou, 2Alexey Castrodad, 2Guillermo Sapiro and 1Lawrence Carin
- Beta-Negative Binomial Process and Poisson Factor Analysis Mingyuan Zhou Lauren A. Hannah
- Hierarchical Bayesian Embeddings for Analysis and Synthesis of High-Dimensional Dynamic Data
