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All publications by Lawrence Carin
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Non-Gaussian Discriminative Factor Models via the Max-Margin Rank-Likelihood
Xin Yuan, Ricardo Henao, Ephraim Tsalik, Raymond Langley and Lawrence Carin
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


A Multitask Point Process Predictive Model
Wenzhao Lian, Ricardo Henao, Vinayak Rao, Joseph Lucas and Lawrence Carin
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Scalable Deep Poisson Factor Analysis for Topic Modeling
Zhe Gan, Changyou Chen, Ricardo Henao, David Carlson and Lawrence Carin
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


GP Kernels for Cross-Spectrum Analysis
Kyle R. Ulrich, David E. Carlson, Kafui Dzirasa and Lawrence Carin
Advances in Neural Information Processing Systems 28, 2015


Preconditioned Spectral Descent for Deep Learning
David E. Carlson, Edo Collins, Ya-ping Hsieh, Lawrence Carin and Volkan Cevher
Advances in Neural Information Processing Systems 28, 2015


Deep Poisson Factor Modeling
Ricardo Henao, Zhe Gan, James Lu and Lawrence Carin
Advances in Neural Information Processing Systems 28, 2015


Large-Scale Bayesian Multi-Label Learning via Topic-Based Label Embeddings
Piyush Rai, Changwei Hu, Ricardo Henao and Lawrence Carin
Advances in Neural Information Processing Systems 28, 2015


On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators
Changyou Chen, Nan Ding and Lawrence Carin
Advances in Neural Information Processing Systems 28, 2015


Deep Temporal Sigmoid Belief Networks for Sequence Modeling
Zhe Gan, Chunyuan Li, Ricardo Henao, David E. Carlson and Lawrence Carin
Advances in Neural Information Processing Systems 28, 2015


Nonlinear Information-Theoretic Compressive Measurement Design
Liming Wang, Abolfazl Razi, Miguel Rodrigues, Robert Calderbank and Lawrence Carin
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Scalable Bayesian Low-Rank Decomposition of Incomplete Multiway Tensors
Piyush Rai, Yingjian Wang, Shengbo Guo, Gary Chen, David Dunson and Lawrence Carin
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Modeling Correlated Arrival Events with Latent Semi-Markov Processes
Wenzhao Lian, Vinayak Rao, Brian Eriksson and Lawrence Carin
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Analysis of Brain States from Multi-Region LFP Time-Series
Kyle R. Ulrich, David E. Carlson, Wenzhao Lian, Jana S. Borg, Kafui Dzirasa and Lawrence Carin
Advances in Neural Information Processing Systems 27, 2014


Bayesian Nonlinear Support Vector Machines and Discriminative Factor Modeling
Ricardo Henao, Xin Yuan and Lawrence Carin
Advances in Neural Information Processing Systems 27, 2014


On the relations of LFPs \& Neural Spike Trains
David E. Carlson, Jana S. Borg, Kafui Dzirasa and Lawrence Carin
Advances in Neural Information Processing Systems 27, 2014


Compressive Sensing of Signals from a GMM with Sparse Precision Matrices
Jianbo Yang, Xuejun Liao, Minhua Chen and Lawrence Carin
Advances in Neural Information Processing Systems 27, 2014


Dynamic Rank Factor Model for Text Streams
Shaobo Han, Lin Du, Esther Salazar and Lawrence Carin
Advances in Neural Information Processing Systems 27, 2014


Exploring the Mind: Integrating Questionnaires and fMRI
Esther Salazar, Ryan Bogdan, Adam Gorka, Ahmad Hariri and Lawrence Carin
Proceedings of the 30th International Conference on Machine Learning (ICML-13), 2013


Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture
Trevor Campbell, Miao Liu, Brian Kulis, Jonathan P. How and Lawrence Carin
Advances in Neural Information Processing Systems 26, 2013


Designed Measurements for Vector Count Data
Liming Wang, David Carlson, Miguel Rodrigues, David Wilcox, Robert Calderbank and Lawrence Carin
Advances in Neural Information Processing Systems 26, 2013


Integrated Non-Factorized Variational Inference
Shaobo Han, Xuejun Liao and Lawrence Carin
Advances in Neural Information Processing Systems 26, 2013


Real-Time Inference for a Gamma Process Model of Neural Spiking
David Carlson, Vinayak Rao, Joshua T. Vogelstein and Lawrence Carin
Advances in Neural Information Processing Systems 26, 2013


Augment-and-Conquer Negative Binomial Processes
Mingyuan Zhou and Lawrence Carin
Advances in Neural Information Processing Systems 25, 2012


Joint Modeling of a Matrix with Associated Text via Latent Binary Features
Xianxing Zhang and Lawrence Carin
Advances in Neural Information Processing Systems 25, 2012


Lognormal and Gamma Mixed Negative Binomial Regression
Mingyuan Zhou, Lingbo Li, Lawrence Carin and David B. Dunson
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Levy Measure Decompositions for the Beta and Gamma Processes
Yingjian Wang and Lawrence Carin
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Inferring Latent Structure From Mixed Real and Categorical Relational Data
Esther Salazar, Matthew Cain, Elise Darling, Stephen Mitroff and Lawrence Carin
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Cross-Domain Multitask Learning with Latent Probit Models
Shaobo Han, Xuejun Liao and Lawrence Carin
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Communications Inspired Linear Discriminant Analysis
Minhua Chen, William Carson, Miguel Rodrigues, Robert Calderbank and Lawrence Carin
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Beta-Negative Binomial Process and Poisson Factor Analysis
Mingyuan Zhou, Lauren Hannah, David B. Dunson and Lawrence Carin
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS-12), 2012


Hierarchical Topic Modeling for Analysis of Time-Evolving Personal Choices
Xianxing Zhang, Lawrence Carin and David B. Dunson
Advances in Neural Information Processing Systems 24, 2011


The Kernel Beta Process
Lu Ren, Yingjian Wang, Lawrence Carin and David B. Dunson
Advances in Neural Information Processing Systems 24, 2011


On the Analysis of Multi-Channel Neural Spike Data
Bo Chen, David E. Carlson and Lawrence Carin
Advances in Neural Information Processing Systems 24, 2011


Tree-Structured Infinite Sparse Factor Model
Xianxing Zhang, Lawrence Carin and David B. Dunson
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


Variational Inference for Stick-Breaking Beta Process Priors
Lawrence Carin, David M. Blei and John W. Paisley
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


The Infinite Regionalized Policy Representation
Miao Liu, Xuejun Liao and Lawrence Carin
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


On the Integration of Topic Modeling and Dictionary Learning
Lingbo Li, Mingyuan Zhou, Guillermo Sapiro and Lawrence Carin
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


Topic Modeling with Nonparametric Markov Tree
Haojun Chen, Lawrence Carin and David B. Dunson
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


The Hierarchical Beta Process for Convolutional Factor Analysis and Deep Learning
Bo Chen, Gungor Polatkan, Guillermo Sapiro, Lawrence Carin and David B. Dunson
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


Dependent Hierarchical Beta Process for Image Interpolation and Denoising
Mingyuan Zhou, Hongxia Yang, Guillermo Sapiro, David B. Dunson and Lawrence Carin
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11), 2011


A Stick-Breaking Construction of the Beta Process
John W. Paisley, Aimee K. Zaas, Christopher W. Woods, Geoffrey S. Ginsburg and Lawrence Carin
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Joint Analysis of Time-Evolving Binary Matrices and Associated Documents
Eric Wang, Dehong Liu, Jorge Silva, Lawrence Carin and David B. Dunson
Advances in Neural Information Processing Systems 23, 2010


Multi-task Reinforcement Learning in Partially Observable Stochastic Environments
Hui Li, Xuejun Liao and Lawrence Carin
Journal of Machine Learning Research, 2009


Nonparametric factor analysis with beta process priors
John W. Paisley and Lawrence Carin
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


Learning to Explore and Exploit in POMDPs
Chenghui Cai, Xuejun Liao and Lawrence Carin
Advances in Neural Information Processing Systems 22, 2009


A Bayesian Model for Simultaneous Image Clustering, Annotation and Object Segmentation
Lan Du, Lu Ren, Lawrence Carin and David B. Dunson
Advances in Neural Information Processing Systems 22, 2009


Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations
Mingyuan Zhou, Haojun Chen, Lu Ren, Guillermo Sapiro, Lawrence Carin and John W. Paisley
Advances in Neural Information Processing Systems 22, 2009


The dynamic hierarchical Dirichlet process
Lu Ren, David B. Dunson and Lawrence Carin
Proceedings of the 25th International Conference on Machine Learning (ICML-08), 2008


Multi-task compressive sensing with Dirichlet process priors
Yuting Qi, Dehong Liu, David B. Dunson and Lawrence Carin
Proceedings of the 25th International Conference on Machine Learning (ICML-08), 2008


Hierarchical kernel stick-breaking process for multi-task image analysis
Qi An, Chunping Wang, Ivo Shterev, Eric Wang, Lawrence Carin and David B. Dunson
Proceedings of the 25th International Conference on Machine Learning (ICML-08), 2008


The matrix stick-breaking process for flexible multi-task learning
Ya Xue, David B. Dunson and Lawrence Carin
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Multi-task learning for sequential data via iHMMs and the nested Dirichlet process
Kai Ni, Lawrence Carin and David B. Dunson
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Quadratically gated mixture of experts for incomplete data classification
Xuejun Liao, Hui Li and Lawrence Carin
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Bayesian compressive sensing and projection optimization
Shihao Ji and Lawrence Carin
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Multi-Task Learning for Classification with Dirichlet Process Priors
Ya Xue, Xuejun Liao, Lawrence Carin and Balaji Krishnapuram
Journal of Machine Learning Research, 2007


Semi-Supervised Multitask Learning
Qiuhua Liu, Xuejun Liao and Lawrence Carin
Advances in Neural Information Processing Systems 20, 2007


Region-based value iteration for partially observable Markov decision processes
Hui Li, Xuejun Liao and Lawrence Carin
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006


Incomplete-data classification using logistic regression
David Williams, Xuejun Liao, Ya Xue and Lawrence Carin
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Logistic regression with an auxiliary data source
Xuejun Liao, Ya Xue and Lawrence Carin
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


On Semi-Supervised Classification
Balaji Krishnapuram, David Williams, Ya Xue, Lawrence Carin, Mário Figueiredo and Alexander J. Hartemink
Advances in Neural Information Processing Systems 17, 2004