Recent Papers

 

Z. Gan, C. Li, C. Chen, Y. Pu, Q. Su, and L. Carin, Scalable Bayesian Learning of Recurrent Neural Networks for Language Modeling, Association for Computational Linguistics (ACL), 2017

 

Z. Gan, C. Gan, X. He, Y. Pu, K. Tran, J. Gao, L. Carin and L. Deng, Semantic Compositional Networks for Visual Captioning, Supplementary Material, IEEE Conf. Computer Vision & Pattern Recognition (CVPR), 2017

 

S. Sun, C. Chen and L.Carin, Learning Structured Weight Uncertainty in Bayesian Neural Networks, Supplementary Material, Artificial Intelligence and Statistics (AISTATS), 2017

 

A. Stevens, Y. Pu, Y. Sun, G. Spell and L. Carin, Tensor-Dictionary Learning with Deep Kruskal-Factor Analysis, Supplementary Material, Artificial Intelligence and Statistics (AISTATS), 2017

 

Q. Su, X. Liao, C. Li, Z. Gan and L. Carin, Unsupervised Learning with Truncated Gaussian Graphical Models, Supplementary Material, Proc. American Association of Artificial Intelligence (AAAI), 2017

 

Y. Zhang, Y. Zhao, L. David, R. Henao and L. Carin, Dynamic Poisson Factor Analysis, IEEE Int. Conf. Data Mining (ICDM), 2016

 

Y. Pu,  Z. Gan,  R. Henao, X. Yuan,  C. Li,  A. Stevens and  L. Carin, Variational Autoencoder for Deep Learning of Images, Labels and Captions, Supplementary Material, Neural and Information Processing Systems (NIPS), 2016

 

Y. Zhang, X. Wang, C. Chen, R. Henao and L. Carin, Towards Unifying Hamiltonian Monte Carlo and Slice Sampling, Supplementary Material, Neural and Information Processing Systems (NIPS), 2016

 

Z. Song, R. Parr, X. Liao, L. Carin, Linear Feature Encoding for Reinforcement Learning, Supplementary Material, Neural and Information Processing Systems (NIPS), 2016

 

C. Chen, N. Ding, C. Li, Y. Zhang, and L. Carin, Stochastic Gradient MCMC with Stale Gradients, Supplementary Material, Neural and Information Processing Systems (NIPS), 2016

 

F. Renna, L. Wang, X. Yuan, J. Yang, G. Reeves, R. Calderbank, L. Carin, and M.R..D. Rodrigues, Classification and Reconstruction of High-Dimensional Signals from Low-Dimensional Noisy Features in the Presence of Side Information, IEEE Trans. Information Theory, 2017

 

Q. Su, X. Liao, C. Chen, L. Carin, Nonlinear Statistical Learning with Truncated Gaussian Graphical Models, Int. Conf. Machine Learning (ICML), 2016

 

J. Song, Z. Gan and L. Carin, Factored Temporal Sigmoid Belief Networks for Sequence Learning, Int. Conf. Machine Learning (ICML), 2016

 

C. Li, A. Stevens, C. Chen, Y. Pu, Z. Gan and L. Carin, Learning Weight Uncertainty with Stochastic Gradient MCMC for Shape Classification, Supplementary Material, Computer Vision & Pattern Recognition (CVPR), 2016

 

L. Wang, M. Chen, M. Rodrigues, D. Wilcox, R. Calderbank and L. Carin, Information-Theoretric Compressive Measurement Design, IEEE Trans. Pattern Analysis Machine Intelligence, 2016

 

Y. Zhang, R. Henao, C. Li and L. Carin, Bayesian Dictionary Learning with Gaussian Processes and Sigmoid Belief Networks, Int. Joint Conference on Artificial Intelligence (IJCAI), 2016.

 

C. Hu, P. Rai and L. Carin, Non-negative Matrix Factorization for Discrete Data with Hierarchical Side-Information, Artificial Intelligence and Statistics (AISTATS), 2016

 

C. Hu, P. Rai and L. Carin, Topic-Based Embeddings for Learning from Large Knowledge Graphs, Supplementary Material, Artificial Intelligence and Statistics (AISTATS), 2016

 

S. Han, X. Liao, D.B. Dunson and L. Carin, Variational Gaussian Copula Inference, Supplementary Material, Artificial Intelligence and Statistics (AISTATS), 2016

 

Z. Song, R. Henao, D. Carlson and L. Carin, Learning Sigmoid Belief Networks via Monte Carlo Expectation Maximization, Supplementary Material, Artificial Intelligence and Statistics (AISTATS), 2016

 

C. Chen, D. Carlson, Z. Gan, C. Li and L. Carin, Bridging the Gap Between Stochastic Gradient MCMC and Stochastic Optimization, Supplementary Material, Artificial Intelligence and Statistics (AISTATS), 2016

 

Y. Pu, X. Yuan, A. Stevens, C. Li, L. Carin, A Deep Generative Deconvolutional Image Model, Supplementary Material, Artificial Intelligence and Statistics (AISTATS), 2016

 

Y. Kaganovsky, I. Odinaka, D. Carlson and L. Carin, Parallel Majorization Minimization with Dynamically Restricted Domains for Nonconvex Optimization, Supplementary Material, Artificial Intelligence and Statistics (AISTATS), 2016

 

R. Henao, J.T. Lu, J.E. Lucas, J. Ferranti and L. Carin, Electronic Health Record Analysis via Deep Poisson Factor Models, J. Machine Learning Research, 2016

 

C. Li, C. Chen, D. Carlson and L. Carin, Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks, Supplementary Material, Proc. American Association of Artificial Intelligence (AAAI), 2016

 

C. Li, C. Chen, K. Fan and L. Carin, High-Order Stochastic Gradient Thermostats for Bayesian Learning of Deep Models, Supplementary Material, Proc. American Association of Artificial Intelligence (AAAI), 2016

 

Y. Zhang, R. Henao, L. Carin, J. Zhong and A.J. Hartemink, Learning a Hybrid Architecture for Sequence Regression and Annotation, Supplementary Material, Proc. American Association of Artificial Intelligence (AAAI), 2016

 

D.E. Carlson, Y.-P. Hsieh, E. Collins, L. Carin and V. Cevher, Stochastic Spectral Descent for Discrete Graphical Models, IEEE Journal of Selected Topics in Signal Processing, 2016.

 

D.E. Carlson, E. Collins, Y.-P. Hsieh, L. Carin and V. Cevher, Preconditioned Spectral Descent for Deep Learning, Supplementary Material, Neural and Information Processing Systems (NIPS), 2015

 

P. Rai, C. Hu, R. Henao, L. Carin, Large-Scale Bayesian Multi-Label Learning via Topic-Based Label Embeddings, Software, Neural and Information Processing Systems (NIPS), 2015

 

K. Ulrich, D.E. Carlson, K. Dzirasa and L. Carin, GP Kernels for Cross-Spectrum Analysis, Supplementary Material, Neural and Information Processing Systems (NIPS), 2015

 

C. Chen, N. Ding and L. Carin, On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators, Supplementary Material, Neural and Information Processing Systems (NIPS), 2015

 

R. Henao, Z. Gan, J. Lu and L. Carin, Deep Poisson Factor Modeling, Supplementary Material, Neural and Information Processing Systems (NIPS), 2015

 

Z. Gan, C. Li, R. Henao, D.E. Carlson and L. Carin, Deep Temporal Sigmoid Belief Networks for Sequence Modeling, Supplementary Material, Neural and Information Processing Systems (NIPS), 2015

 

Y. Kaganovsky, S. Han, S. Degirmenci, D.G. Politte, D.J. Brady, J.A. O’Sullivan, and L. Carin, Alternating Minimization Algorithm with Automatic Relevance Determination for Transmission Tomography under Poisson Noise, SIAM J. Imaging Sciences, 2015

 

L. Wang, J. Huang, X. Yuan, K. Krishnamurthy, J. Greenberg, V. Cevher, M.R.D. Rodrigues, D. Brady, R. Calderbank, and L. Carin, Signal Recovery and System Calibration from Multiple Compressive Poisson Measurements, SIAM J. Imaging Sciences, 2015

 

C. Hu, P. Rai and L. Carin, Zero-Truncated Poisson Tensor Factorization for Massive Binary Tensors, Uncertainty in Artificial Intelligence (UAI), 2015

 

C. Hu, P. Rai, C. Chen, M. Harding, and L. Carin, Scalable Bayesian Non-Negative Tensor Factorization for Massive Count Data, European Conference on Machine Learning (ECML), 2015

 

X. Yuan, R. Henao, E.L. Tsalik, R.J. Langley and L. Carin, Non-Gaussian Discriminative Factor Models via the Max-Margin Rank-Likelihood, Supplementary Material, Int. Conf. Machine Learning (ICML), 2015

 

W. Lian, R. Henao, V. Rao, J. Lucas and L. Carin, A Multitask Point Process Predictive Model, Supplementary Material, Int. Conf. Machine Learning (ICML), 2015

 

Z. Gan, C. Chen, R. Henao, D. Carlson and L. Carin, Scalable Deep Poisson Factor Analysis for Topic Modeling, Supplementary Material, Int. Conf. Machine Learning (ICML), 2015

 

P. Rai, C. Hu , M. Harding and L. Carin, Scalable Probabilistic Tensor Factorization for Binary and Count Data, Int. Joint Conf. on Artificial Intelligence (IJCAI), 2015

 

M. Liu, J.P. How, C. Amato, X. Liao and L. Carin, Stick-Breaking Policy Learning in Dec-POMDPs, Int. Joint Conf. on Artificial Intelligence (IJCAI), 2015

 

W. Lian, R. Talmon, H. Zaveri, L. Carin and R. Coifman, Multivariate Time-Series Analysis and Diffusion Maps, Signal Processing, 2015

 

Z. Gan, R. Henao, D. Carlson and L. Carin, Learning Deep Sigmoid Belief Networks with Data Augmentation, Supplementary Material, Artificial Intelligence and Statistics (AISTATS), 2015

 

D. Carlson, V. Cevher and L. Carin, Stochastic Spectral Descent for Restricted Boltzmann Machines, Supplementary Material, Artificial Intelligence and Statistics (AISTATS), 2015

 

X. Yuan, T.-H. Tsai, R. Zhu, P. Llull, D. Brady, and L. Carin, Compressive Hyperspectral Imaging with Side Information, Appendix, to appear in IEEE J. Selected Topics Signal Processing, 2015

 

Yi Zhen, P. Rai, H. Zha and L. Carin, Cross-Modal Similarity Learning via Pairs, Preferences, and Active Supervision, AAAI Conference on Artificial Intelligence, 2015

 

P. Rai, Y. Wang, and L. Carin, Leveraging Features and Networks for Probabilistic Tensor Decomposition, AAAI Conference on Artificial Intelligence, 2015

 

W. Lian, P. Rai, E. Salazar, and L. Carin, Integrating Features and Similarities: Flexible Models for Heterogeneous Multiview Data, AAAI Conference on Artificial Intelligence, 2015

 

E. Salazar, Y. Nikolova, W. Lian, P. Rai, A.L. Romer, A.R. Hariri, and L. Carin, A Bayesian Framework for Multi-Modality Analysis of Mental Health, Supplementary Material, submitted

 

K. Ulrich, D.E. Carlson, W. Lian, J.S. Borg, K. Dzirasa and L. Carin, Analysis of Brain States from Multi-Region LFP Time-Series, Supplementary Material, Neural Information Processing Systems (NIPS), 2014

 

J. Yang, X. Liao, M. Chen and L. Carin, Compressive Sensing of Signals from a GMM with Sparse Precision Matrices, Supplementary Material, Neural Information Processing Systems (NIPS), 2014

 

D.E. Carlson, J. Schaich Borg, K. Dzirasa, and L. Carin, On the Relationship Between LFP & Spiking Data, Supplementary Material, Neural Information Processing Systems (NIPS), 2014

 

S. Han , L. Du , E. Salazar and L. Carin, Dynamic Rank Factor Model for Text Streams, Supplementary Material, Neural Information Processing Systems (NIPS), 2014

 

R. Henao, X. Yuan and L. Carin, Bayesian Nonlinear Support Vector Machines and Discriminative Factor Modeling, Supplementary Material, Neural Information Processing Systems (NIPS), 2014

 

X. Yuan, V. Rao, S. Han and L. Carin, Hierarchical Infinite Divisibility for Multiscale Shrinkage, (Supplementary Material), (Code), accepted for publication in IEEE Trans. Signal Processing

 

J. Yang, X. Liao, X. Yuan, P. Llull, D.J. Brady, G. Sapiro, and L. Carin, Compressive Sensing by Learning a Gaussian Mixture Model from Measurements, accepted for publication in IEEE Trans. Image Processing

 

L. Wang, A. Razi, M.D. Rodrigues, R. Calderbank and L. Carin, Nonlinear Information-Theoretic Compressive Measurement Design (Supplementary Material), Proc. Int. Conf. Machine Learning (ICML), 2014

 

P. Rai, Y.Wang, S. Guoz, G. Chen, D. Dunson and L. Carin, Scalable Bayesian Low-Rank Decomposition of Incomplete Multiway Tensors (Supplementary Material), Proc. Int. Conf. Machine Learning (ICML), 2014

 

W. Lian, V. Rao, B. Eriksson, L. Carin, Modeling Correlated Arrival Events with Latent Semi-Markov Processes, Proc. Int. Conf. Machine Learning (ICML), 2014

 

J. Yang, X. Yuan, X. Liao, P. Llull, D.J. Brady, G. Sapiro and L. Carin, Video Compressive Sensing Using Gaussian Mixture Models, (Software), to appear in IEEE Trans. Image Processing, 2014

 

H. Zhang and L. Carin, Multi-Shot Imaging: Joint Alignment, Deblurring and Resolution-Enhancement, IEEE Computer Vision and Pattern Recognition (CVPR), 2014

 

X. Yuan, P. Llull, X. Liao, J. Yang, G. Sapiro, D.J. Brady and L. Carin, Low-Cost Compressive Sensing for Color Video and Depth, IEEE Computer Vision and Pattern Recognition (CVPR), 2014

 

C. Hu, E. Ryu, D. Carlson, Y. Wang and L. Carin, Latent Gaussian Models for Topic Modeling, Artificial Intelligence & Statistics (AISTATS), 2014

 

X. Liao, H. Li, and L. Carin, Generalized Alternating Projection for Weighted-ℓ2,1 Minimization with Applications to Model-Based Compressive Sensing, to appear in SIAM J. Imaging Science, 2014

 

L. Wang, D. Carlson, M.R.D. Rodrigues, R. Calderbank and L. Carin, A Bregman Matrix and the Gradient of Mutual Information for Vector Poisson and Gaussian Channels, to appear in IEEE Trans. Information Theory, 2014

 

F. Renna, R. Calderbank, L. Carin, and M.R.D. Rodrigues, Reconstruction of Signals Drawn from a Gaussian Mixture via Noisy Compressive Measurements, to appear IEEE Trans. Signal Processing, 2014.

 

Z. Xing, B. Nicholson, M. Jimenez, T. Veldman, L. Hudson, J. Lucas, D. Dunson, A.K. Zaas, C.W. Woods, G.S. Ginsburg  and L. Carin, Bayesian Modeling of Space-Time Properties of Infectious Disease in a College Student Population, to appear in J. Applied Statistics, 2014

 

M. Zhou and L. Carin, Negative Binomial Process Count and Mixture Modeling, to appear in IEEE Trans. Pattern Analysis Machine Intelligence, 2014

 

T. Campbell, M. Liu, B. Kulis, J.P. How, L. Carin, Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture, Neural Information Processing Systems (NIPS), 2013

 

L. Wang, D. Carlson, M.D. Rodrigues, D. Wilcox, R. Calderbank and L. Carin, Designed Measurements for Vector Count Data, (Supplementary Material), Neural Information Processing Systems (NIPS), 2013

 

S. Han, X. Liao and L. Carin, Integrated Non-Factorized Variational Inference (Supplementary Material), Neural Information Processing Systems (NIPS), 2013

 

D. Carlson, V. Rao, J. Vogelstein and L. Carin, Real-Time Inference for a Gamma Process Model of Neural Spiking, Neural Information Processing Systems (NIPS), 2013

 

D. Carlson, J. Vogelstein, Q.Wu, W. Lian, M. Zhou, C.R. Stoetzner, D. Kipke, D. Weber, D. Dunson and L. Carin, Sorting Electrophysiological Data via Dictionary Learning & Mixture Modeling, IEEE Trans. Biomedical Engineering, 2013

 

E. Salazar, D.B. Dunson, and L. Carin, Analysis of Space-Time Relational Data with Application to Legislative Voting, Computational Statistics and Data Analysis, 2013

 

M. Liu, X. Liao and L. Carin, Online Expectation Maximization for Reinforcement Learning in POMDPs, Prof. Int. Joint Conf. Artificial Intelligence (IJCAI), 2013

 

P. Llull, X. Liao, X. Yuan, J. Yang, D. Kittle, L. Carin, G. Sapiro and D.J. Brady, Coded Aperture Compressive Temporal Imaging, Optics Express, 2013.

 

E. Salazar, R. Bogdan, A. Gorka, A.R. Hariri and L. Carin, Exploring the Mind: Integrating Questionnaires and fMRI, Proc. Int. Conf. Machine Learning (ICML), 2013

 

A. Rajwade, D. Kittle, T.-H. Tsai, D. Brady and L. Carin, Coded Hyperspectral Imaging and Blind Compressive Sensing, SIAM J. Imaging Science, 2013

 

B. Chen, G. Polatkan, G. Sapiro, D. Blei, D. Dunson and L. Carin, Deep Learning with Hierarchical Convolutional Factor Analysis (supplementary material), IEEE Trans. Pattern Analysis & Machine Intelligence, 2013.

 

E. Wang, E. Salazar, D. Dunson and L. Carin, Spatio-Temporal Modeling of Legislation and Votes, Bayesian Analysis, 2013.

 

M. Zhou and L. Carin, Augment-and-Conquer Negative Binomial Processes, Proc. Neural and Information Processing Systems (NIPS), 2012

 

X. Zhang and L. Carin, Joint Modeling of a Matrix with Associated Text via Latent Binary Features (Supplementary Material), Proc. Neural and Information Processing Systems (NIPS), 2012

 

L. Li, X. Zhang, M. Zhou and L. Carin, Nested Dictionary Learning for Hierarchical Organization of Imagery and Text (Supplementary Material), Proc. Uncertainty in Artificial Intelligence (UAI), 2012

 

M. Ding, L. He, D. Dunson and L. Carin, Nonparametric Bayesian Segmentation of Multivariate Inhomogeneous Space-Time Poisson Process, Bayesian Analysis, 2012

 

W.R. Carson, M. Chen, M.R.D. Rodrigues, R. Calderbank and L. Carin, Communications Inspired Projection Design with Application to Compressive Sensing, SIAM J. Imaging Sciences, 2012

 

Y. Wang and L. Carin, Levy Measure Decompositions for the Beta and Gamma Processes (Supplementary material), Proc. Int. Conf. Machine Learning (ICML), 2012

 

S. Han, X. Liao, L. Carin, Cross-Domain Multitask Learning with Latent Probit Models, Proc. Int. Conf. Machine Learning (ICML), 2012

 

M. Chen, W. Carson, M. Rodrigues, R. Calderbank and L. Carin, Communications Inspired Linear Discriminant Analysis, Proc. Int. Conf. Machine Learning (ICML), 2012

 

M. Zhou, L. Li, D. Dunson, and L. Carin, Lognormal and Gamma Mixed Negative Binomial Regression (Supplementary Material), Proc. Int. Conf. Machine Learning (ICML), 2012

 

E. Salazar, M.S. Cain, E.F. Darling, S.R. Mitroff and L.Carin, Inferring Latent Structure From Mixed Real and Categorical Relational Data, Proc. Int. Conf. Machine Learning (ICML), 2012

 

X. Chen, M. Zhou,  and L. Carin, The Contextual Focused Topic Model, Proc. ACM SIGKDD Conf. Knowledge Discovery and Data Mining, 2012

 

J. Silva and L. Carin, Active Learning for Online Bayesian Matrix Factorization, Proc. ACM SIGKDD Conf. Knowledge Discovery and Data Mining, 2012

 

M. Zhou, L. Hannah, D. Dunson and L. Carin, Beta-Negative Binomial Process and Poisson Factor Analysis, AISTATS 2012

 

X. Zhang, D.B. Dunson, and L. Carin, Hierarchical Topic Modeling for Analysis of Time-Evolving Personal Choices, (Supplementary Materials), Proc. Neural and Information Processing Systems (NIPS), 2011

 

L. Ren, Y. Wang, D. Dunson and L. Carin, The Kernel Beta Process (Supplementary Material), Proc. Neural and Information Processing Systems (NIPS), 2011

 

B. Chen, D.E. Carlson and L. Carin, On the Analysis of Multi-Channel Neural Spike Data, Proc. Neural and Information Processing Systems (NIPS), 2011

 

M. Chen, A. Zaas, C. Woods, G.S. Ginsburg, J. Lucas, D. Dunson and L. Carin, Predicting Viral Infection from High-Dimensional Biomarker Trajectories, J. Am. Statistical Association, 2011

 

Z. Xing, M. Zhou, A. Castrodad, G. Sapiro and L. Carin, Dictionary Learning for Noisy and Incomplete Hyperspectral Images, SIAM J. Imaging Sciences, 2011

 

M. Liu, X. Liao and L. Carin, The Infinite Regionalized Policy Representation, Proc. Int. Conf. Machine Learning (ICML), 2011

 

J. Paisley, L. Carin and D. Blei, Variational Inference for Stick-Breaking Beta Process Priors, Proc. Int. Conf. Machine Learning (ICML), 2011

 

X. Zhang, D.B. Dunson and L. Carin, Tree-Structured Infinite Sparse Factor Model, (Supplemental Material), Proc. Int. Conf. Machine Learning (ICML), 2011

 

L. Li, M. Zhou, G. Sapiro and L. Carin, On the Integration of Topic Modeling and Dictionary Learning, Proc. Int. Conf. Machine Learning (ICML), 2011

 

H. Chen, D.B. Dunson and L. Carin, Topic Modeling with Nonparametric Markov Tree, Proc. Int. Conf. Machine Learning (ICML), 2011

 

B. Chen, G. Polatkan, G. Sapiro, D. Dunson and L. Carin, The Hierarchical Beta Process for Convolutional Factor Analysis and Deep Learning, Proc. Int. Conf. Machine Learning (ICML), 2011

 

M. Zhou, H. Yang, G. Sapiro, D. Dunson and L. Carin, Dependent Hierarchical Beta Process for Image Interpolation and Denoising, AISTATS, 2011

 

X. Ding, L. He and L. Carin, Bayesian Robust Principal Component Analysis, IEEE Trans. Image Processing, 2011

 

M. Zhou, H. Chen, J. Paisley, L. Ren, L. Li, Z. Xing, D. Dunson, G. Sapiro and L. Carin, Nonparametric Bayesian Dictionary Learning for Analysis of Noisy and Incomplete Images, IEEE Trans. Image Processing, 2011

 

L. Ren, L. Du, L. Carin and D. Dunson, Logistic Stick-Breaking Process, J. Machine Learning Research (code is here), 2011

 

L. Carin, D. Liu and B. Guo, Coherence, Compressive Sensing and Random Sensor Arrays, to appear in IEEE Antennas and Propagation Magazine, 2011

 

C. Wang, X. Liao, D. Dunson and L. Carin, Multi-Task Learning for Incomplete Data, J. Machine Learning Research, 2010

 

E. Wang, D. Liu, J. Silva, D. Dunson and L. Carin, Joint Analysis of Time-Evolving Binary Matrices and Associated Documents, Proc. Neural and Information Processing Systems (NIPS), 2010

 

M. Zhou, C. Wang, M. Chen, J. Paisley, D. Dunson and L. Carin, Nonparametric Bayesian Matrix Completion, 2010 IEEE Sensor Array and Multichannel Signal Processing Workshop

 

L. Du, M. Chen, J. Lucas and L. Carin, Sticky Hidden Markov Modeling of Comparative Genomic Hybridization, IEEE Trans. Signal Processing, 2010.

 

M. Chen, D. Carlson, A. Zaas, C. Woods, G.S. Ginsburg, J. Lucas and L. Carin, Detection of viruses via statistical gene-expression analysis, accepted for publication in IEEE Trans. Biomedical Engineering

 

J. Paisley, A. Zaas, C.W. Woods, G.S. Ginsburg and L. Carin, A Stick-Breaking Construction of the Beta Process, Int. Conf. Machine Learning (ICML), June 2010

 

J. Paisley, X. Liao and L. Carin, Active learning and basis selection for kernel-based linear models: A Bayesian perspective, IEEE Trans. Signal Processing, 2010.

 

M. Zhou, H. Chen, J. Paisley, L. Ren, G. Sapiro and L. Carin, Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations, Neural and Information Processing Systems (NIPS), 2009.

 

L. Du, L. Ren, D. Dunson and L. Carin, A Bayesian Model for Simultaneous Image Clustering, Annotation and Object Segmentation, Neural and Information Processing Systems (NIPS), 2009.

 

C. Cai, X. Liao, and L. Carin, Learning to Explore and Exploit in POMDPs, Neural and Information Processing Systems (NIPS), 2009.

 

B. Chen, M. Chen, J. Paisley, A. Zaas, C. Woods, G.S. Ginsburg, A. Hero III, J. Lucas, D. Dunson and L. Carin, Nonparametric Bayesian Factor Analysis: Application to Time-Evolving Viral Gene-Expression Data, BMC Bioinformatics, 2010

 

M. Chen, J. Silva, J. Paisley, C. Wang, D. Dunson and L. Carin, Compressive Sensing on Manifolds Using a Nonparametric Mixture of Factor Analyzers: Algorithm and Performance Bounds, IEEE Trans. Signal Processing, 2010

 

L. He, H. Chen and L. Carin, Tree-Structured Compressive Sensing with Variational Bayesian Analysis, IEEE Signal Processing Letters, 2009

 

L. Ren, D. Dunson, S. Lindroth and L. Carin, Dynamic Nonparametric Bayesian Models for Analysis of Music, J. American Statistical Association (JASA), 2010.

 

I. Pruteanu-Malinici, L. Ren, J. Paisley, E. Wang and L. Carin, Hierarchical Bayesian Modeling of Topics in Time-Stamped Documents, IEEE Trans. Pattern Analysis Machine Intelligence, 2010.

 

J. Paisley and L. Carin, Hidden Markov Models with Stick-Breaking Priors, IEEE Trans. Signal Processing, 2010

 

J. Paisley and L. Carin, Nonparametric Factor Analysis with Beta Process Priors, Proc. Int. Conf. Machine Learning (ICML), 2009

 

H. Li, X. Liao and L. Carin, Multi-task Reinforcement Learning in Partially Observable Stochastic Environments, J. Machine Learning Research, 2009

 

L. Carin, On the Relationship Between Compressive Sensing and Random Sensor Arrays, IEEE Antennas & Propagation Magazine, October 2009.

 

Q. Liu, X. Liao, H. Li, J. Stack and L. Carin, Semi-Supervised Multitask Learning, IEEE Trans. Pattern Analysis & Machine Intelligence, 2009

 

L. He and L. Carin, Exploiting Structure in Wavelet-Based Bayesian Compressive Sensing, IEEE Trans. Signal Processing, Sept 2009