Carin, Lawrence

194 publications

NeurIPS 2025 Coupling Generative Modeling and an Autoencoder with the Causal Bridge Ruolin Meng, Ming-Yu Chung, Dhanajit Brahma, Ricardo Henao, Lawrence Carin

NeurIPS 2025 From SoftMax to Score: Transformers Can Effectively Implement In-Context Denoising Steps Paul Rosu, Lawrence Carin, Xiang Cheng

ICLR 2025 Graph Transformers Dream of Electric Flow Xiang Cheng, Lawrence Carin, Suvrit Sra

ICML 2025 On Understanding Attention-Based In-Context Learning for Categorical Data Aaron T Wang, William Convertino, Xiang Cheng, Ricardo Henao, Lawrence Carin

WACV 2024 Meta-Learned Attribute Self-Interaction Network for Continual and Generalized Zero-Shot Learning Vinay Verma, Nikhil Mehta, Kevin J. Liang, Aakansha Mishra, Lawrence Carin

WACV 2023 Pushing the Efficiency Limit Using Structured Sparse Convolutions Vinay Kumar Verma, Nikhil Mehta, Shijing Si, Ricardo Henao, Lawrence Carin

UAI 2022 Capturing Actionable Dynamics with Structured Latent Ordinary Differential Equations Paidamoyo Chapfuwa, Sherri Rose, Lawrence Carin, Edward Meeds, Ricardo Henao

ICLR 2022 Gradient Importance Learning for Incomplete Observations Qitong Gao, Dong Wang, Joshua David Amason, Siyang Yuan, Chenyang Tao, Ricardo Henao, Majda Hadziahmetovic, Lawrence Carin, Miroslav Pajic

WACV 2022 Learning to Weight Filter Groups for Robust Classification Siyang Yuan, Yitong Li, Dong Wang, Ke Bai, Lawrence Carin, David Carlson

AISTATS 2021 Continual Learning Using a Bayesian Nonparametric Dictionary of Weight Factors Nikhil Mehta, Kevin Liang, Vinay Kumar Verma, Lawrence Carin

AISTATS 2021 Counterfactual Representation Learning with Balancing Weights Serge Assaad, Shuxi Zeng, Chenyang Tao, Shounak Datta, Nikhil Mehta, Ricardo Henao, Fan Li, Lawrence Carin

NeurIPS 2021 CAM-GAN: Continual Adaptation Modules for Generative Adversarial Networks Sakshi Varshney, Vinay Kumar Verma, P. K. Srijith, Lawrence Carin, Piyush Rai

CVPR 2021 Efficient Feature Transformations for Discriminative and Generative Continual Learning Vinay Kumar Verma, Kevin J Liang, Nikhil Mehta, Piyush Rai, Lawrence Carin

ICLR 2021 FairFil: Contrastive Neural Debiasing Method for Pretrained Text Encoders Pengyu Cheng, Weituo Hao, Siyang Yuan, Shijing Si, Lawrence Carin

AAAI 2021 GO Hessian for Expectation-Based Objectives Yulai Cong, Miaoyun Zhao, Jianqiao Li, Junya Chen, Lawrence Carin

ICLR 2021 Improving Zero-Shot Voice Style Transfer via Disentangled Representation Learning Siyang Yuan, Pengyu Cheng, Ruiyi Zhang, Weituo Hao, Zhe Gan, Lawrence Carin

AAAI 2021 Learning Graphons via Structured Gromov-Wasserstein Barycenters Hongteng Xu, Dixin Luo, Lawrence Carin, Hongyuan Zha

ICLR 2021 MixKD: Towards Efficient Distillation of Large-Scale Language Models Kevin J Liang, Weituo Hao, Dinghan Shen, Yufan Zhou, Weizhu Chen, Changyou Chen, Lawrence Carin

NeurIPS 2021 Supercharging Imbalanced Data Learning with Energy-Based Contrastive Representation Transfer Junya Chen, Zidi Xiu, Benjamin Goldstein, Ricardo Henao, Lawrence Carin, Chenyang Tao

CVPRW 2021 Towards Fair Federated Learning with Zero-Shot Data Augmentation Weituo Hao, Mostafa El-Khamy, Jungwon Lee, Jianyi Zhang, Kevin J. Liang, Changyou Chen, Lawrence Carin

CVPR 2021 Wasserstein Contrastive Representation Distillation Liqun Chen, Dong Wang, Zhe Gan, Jingjing Liu, Ricardo Henao, Lawrence Carin

WACV 2021 Zero-Shot Recognition via Optimal Transport Wenlin Wang, Hongteng Xu, Guoyin Wang, Wenqi Wang, Lawrence Carin

NeurIPS 2020 AutoSync: Learning to Synchronize for Data-Parallel Distributed Deep Learning Hao Zhang, Yuan Li, Zhijie Deng, Xiaodan Liang, Lawrence Carin, Eric P. Xing

AAAI 2020 Bridging Maximum Likelihood and Adversarial Learning via Α-Divergence Miaoyun Zhao, Yulai Cong, Shuyang Dai, Lawrence Carin

ICML 2020 CLUB: A Contrastive Log-Ratio Upper Bound of Mutual Information Pengyu Cheng, Weituo Hao, Shuyang Dai, Jiachang Liu, Zhe Gan, Lawrence Carin

NeurIPS 2020 Calibrating CNNs for Lifelong Learning Pravendra Singh, Vinay Kumar Verma, Pratik Mazumder, Lawrence Carin, Piyush Rai

ICLR 2020 Collaborative Filtering with a Synthetic Feedback Loop Wenlin Wang, Hongteng Xu, Ruiyi Zhang, Wenqi Wang, Lawrence Carin

AAAI 2020 Complementary Auxiliary Classifiers for Label-Conditional Text Generation Yuan Li, Chunyuan Li, Yizhe Zhang, Xiujun Li, Guoqing Zheng, Lawrence Carin, Jianfeng Gao

AAAI 2020 Dynamic Embedding on Textual Networks via a Gaussian Process Pengyu Cheng, Yitong Li, Xinyuan Zhang, Liqun Chen, David E. Carlson, Lawrence Carin

NeurIPSW 2020 Estimating Total Correlation with Mutual Information Bounds Pengyu Cheng, Weituo Hao, Lawrence Carin

NeurIPS 2020 GAN Memory with No Forgetting Yulai Cong, Miaoyun Zhao, Jianqiao Li, Sijia Wang, Lawrence Carin

ICML 2020 Graph Optimal Transport for Cross-Domain Alignment Liqun Chen, Zhe Gan, Yu Cheng, Linjie Li, Lawrence Carin, Jingjing Liu

AAAI 2020 Graph-Driven Generative Models for Heterogeneous Multi-Task Learning Wenlin Wang, Hongteng Xu, Zhe Gan, Bai Li, Guoyin Wang, Liqun Chen, Qian Yang, Wenqi Wang, Lawrence Carin

ICML 2020 Learning Autoencoders with Relational Regularization Hongteng Xu, Dixin Luo, Ricardo Henao, Svati Shah, Lawrence Carin

AISTATS 2020 Nested-Wasserstein Self-Imitation Learning for Sequence Generation Ruiyi Zhang, Changyou Chen, Zhe Gan, Zheng Wen, Wenlin Wang, Lawrence Carin

ICML 2020 On Leveraging Pretrained GANs for Generation with Limited Data Miaoyun Zhao, Yulai Cong, Lawrence Carin

NeurIPS 2020 Perturbing Across the Feature Hierarchy to Improve Standard and Strict Blackbox Attack Transferability Nathan Inkawhich, Kevin Liang, Binghui Wang, Matthew Inkawhich, Lawrence Carin, Yiran Chen

ICLR 2020 RaCT: Toward Amortized Ranking-Critical Training for Collaborative Filtering Sam Lobel, Chunyuan Li, Jianfeng Gao, Lawrence Carin

ICLR 2020 RaCT: Toward Amortized Ranking-Critical Training for Collaborative Filtering Sam Lobel, Chunyuan Li, Jianfeng Gao, Lawrence Carin

NeurIPS 2020 Reconsidering Generative Objectives for Counterfactual Reasoning Danni Lu, Chenyang Tao, Junya Chen, Fan Li, Feng Guo, Lawrence Carin

AAAI 2020 Sequence Generation with Optimal-Transport-Enhanced Reinforcement Learning Liqun Chen, Ke Bai, Chenyang Tao, Yizhe Zhang, Guoyin Wang, Wenlin Wang, Ricardo Henao, Lawrence Carin

AISTATS 2020 Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory Jianyi Zhang, Ruiyi Zhang, Lawrence Carin, Changyou Chen

MLHC 2020 Students Need More Attention: BERT-Based Attention Model for Small Data with Application to Automatic Patient Message Triage Shijing Si, Rui Wang, Jedrek Wosik, Hao Zhang, David Dov, Guoyin Wang, Lawrence Carin

ICLR 2020 Transferable Perturbations of Deep Feature Distributions Nathan Inkawhich, Kevin J Liang, Lawrence Carin, Yiran Chen

AISTATS 2019 Adversarial Learning of a Sampler Based on an Unnormalized Distribution Chunyuan Li, Ke Bai, Jianqiao Li, Guoyin Wang, Changyou Chen, Lawrence Carin

NeurIPS 2019 Certified Adversarial Robustness with Additive Noise Bai Li, Changyou Chen, Wenlin Wang, Lawrence Carin

AAAI 2019 Communication-Efficient Stochastic Gradient MCMC for Neural Networks Chunyuan Li, Changyou Chen, Yunchen Pu, Ricardo Henao, Lawrence Carin

ICLR 2019 GO Gradient for Expectation-Based Objectives Yulai Cong, Miaoyun Zhao, Ke Bai, Lawrence Carin

ICLR 2019 Improving Sequence-to-Sequence Learning via Optimal Transport Liqun Chen, Yizhe Zhang, Ruiyi Zhang, Chenyang Tao, Zhe Gan, Haichao Zhang, Bai Li, Dinghan Shen, Changyou Chen, Lawrence Carin

NeurIPS 2019 Improving Textual Network Learning with Variational Homophilic Embeddings Wenlin Wang, Chenyang Tao, Zhe Gan, Guoyin Wang, Liqun Chen, Xinyuan Zhang, Ruiyi Zhang, Qian Yang, Ricardo Henao, Lawrence Carin

NeurIPS 2019 Kernel-Based Approaches for Sequence Modeling: Connections to Neural Methods Kevin Liang, Guoyin Wang, Yitong Li, Ricardo Henao, Lawrence Carin

AISTATS 2019 On Connecting Stochastic Gradient MCMC and Differential Privacy Bai Li, Changyou Chen, Hao Liu, Lawrence Carin

NeurIPS 2019 On Fenchel Mini-Max Learning Chenyang Tao, Liqun Chen, Shuyang Dai, Junya Chen, Ke Bai, Dong Wang, Jianfeng Feng, Wenlian Lu, Georgiy Bobashev, Lawrence Carin

NeurIPS 2019 Ouroboros: On Accelerating Training of Transformer-Based Language Models Qian Yang, Zhouyuan Huo, Wenlin Wang, Lawrence Carin

ICML 2019 Revisiting the SoftMax Bellman Operator: New Benefits and New Perspective Zhao Song, Ron Parr, Lawrence Carin

NeurIPS 2019 Scalable Gromov-Wasserstein Learning for Graph Partitioning and Matching Hongteng Xu, Dixin Luo, Lawrence Carin

AISTATS 2019 Scalable Thompson Sampling via Optimal Transport Ruiyi Zhang, Zheng Wen, Changyou Chen, Chen Fang, Tong Yu, Lawrence Carin

MLHC 2019 Thyroid Cancer Malignancy Prediction from Whole Slide Cytopathology Images David Dov, Shahar Z. Kovalsky, Jonathan Cohen, Danielle Elliott Range, Ricardo Henao, Lawrence Carin

AAAI 2018 Adaptive Feature Abstraction for Translating Video to Text Yunchen Pu, Martin Renqiang Min, Zhe Gan, Lawrence Carin

NeurIPS 2018 Adversarial Text Generation via Feature-Mover's Distance Liqun Chen, Shuyang Dai, Chenyang Tao, Haichao Zhang, Zhe Gan, Dinghan Shen, Yizhe Zhang, Guoyin Wang, Ruiyi Zhang, Lawrence Carin

AISTATS 2018 Benefits from Superposed Hawkes Processes Hongteng Xu, Dixin Luo, Xu Chen, Lawrence Carin

AAAI 2018 Deconvolutional Latent-Variable Model for Text Sequence Matching Dinghan Shen, Yizhe Zhang, Ricardo Henao, Qinliang Su, Lawrence Carin

NeurIPS 2018 Diffusion Maps for Textual Network Embedding Xinyuan Zhang, Yitong Li, Dinghan Shen, Lawrence Carin

NeurIPS 2018 Distilled Wasserstein Learning for Word Embedding and Topic Modeling Hongteng Xu, Wenlin Wang, Wei Liu, Lawrence Carin

ICML 2018 Learning Registered Point Processes from Idiosyncratic Observations Hongteng Xu, Lawrence Carin, Hongyuan Zha

AISTATS 2018 Learning Structural Weight Uncertainty for Sequential Decision-Making Ruiyi Zhang, Chunyuan Li, Changyou Chen, Lawrence Carin

MLHC 2018 Multi-Label Learning from Medical Plain Text with Convolutional Residual Models Yinyuan Zhang, Ricardo Henao, Zhe Gan, Yitong Li, Lawrence Carin

IJCAI 2018 Online Continuous-Time Tensor Factorization Based on Pairwise Interactive Point Processes Hongteng Xu, Dixin Luo, Lawrence Carin

ICML 2018 Policy Optimization as Wasserstein Gradient Flows Ruiyi Zhang, Changyou Chen, Chunyuan Li, Lawrence Carin

MLHC 2018 Predicting Smoking Events with a Time-Varying Semi-Parametric Hawkes Process Model Matthew Engelhard, Hongteng Xu, Lawrence Carin, Jason A. Oliver, Matthew Hallyburton, F. Joseph McClernon

AISTATS 2018 Symmetric Variational Autoencoder and Connections to Adversarial Learning Liqun Chen, Shuyang Dai, Yunchen Pu, Erjin Zhou, Chunyuan Li, Qinliang Su, Changyou Chen, Lawrence Carin

AISTATS 2018 Topic Compositional Neural Language Model Wenlin Wang, Zhe Gan, Wenqi Wang, Dinghan Shen, Jiaji Huang, Wei Ping, Sanjeev Satheesh, Lawrence Carin

AAAI 2018 Video Generation from Text Yitong Li, Martin Renqiang Min, Dinghan Shen, David E. Carlson, Lawrence Carin

AAAI 2018 Zero-Shot Learning via Class-Conditioned Deep Generative Models Wenlin Wang, Yunchen Pu, Vinay Kumar Verma, Kai Fan, Yizhe Zhang, Changyou Chen, Piyush Rai, Lawrence Carin

NeurIPS 2017 A Probabilistic Framework for Nonlinearities in Stochastic Neural Networks Qinliang Su, Xuejun Liao, Lawrence Carin

NeurIPS 2017 ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching Chunyuan Li, Hao Liu, Changyou Chen, Yuchen Pu, Liqun Chen, Ricardo Henao, Lawrence Carin

ICLR 2017 Adaptive Feature Abstraction for Translating Video to Language Yunchen Pu, Martin Renqiang Min, Zhe Gan, Lawrence Carin

ICML 2017 Adversarial Feature Matching for Text Generation Yizhe Zhang, Zhe Gan, Kai Fan, Zhi Chen, Ricardo Henao, Dinghan Shen, Lawrence Carin

NeurIPS 2017 Adversarial Symmetric Variational Autoencoder Yuchen Pu, Weiyao Wang, Ricardo Henao, Liqun Chen, Zhe Gan, Chunyuan Li, Lawrence Carin

NeurIPS 2017 An Inner-Loop Free Solution to Inverse Problems Using Deep Neural Networks Kai Fan, Qi Wei, Lawrence Carin, Katherine A. Heller

NeurIPS 2017 Cross-Spectral Factor Analysis Neil Gallagher, Kyle R Ulrich, Austin Talbot, Kafui Dzirasa, Lawrence Carin, David E Carlson

NeurIPS 2017 Deconvolutional Paragraph Representation Learning Yizhe Zhang, Dinghan Shen, Guoyin Wang, Zhe Gan, Ricardo Henao, Lawrence Carin

ICML 2017 Deep Generative Models for Relational Data with Side Information Changwei Hu, Piyush Rai, Lawrence Carin

AISTATS 2017 Learning Structured Weight Uncertainty in Bayesian Neural Networks Shengyang Sun, Changyou Chen, Lawrence Carin

NeurIPS 2017 Scalable Model Selection for Belief Networks Zhao Song, Yusuke Muraoka, Ryohei Fujimaki, Lawrence Carin

CVPR 2017 Semantic Compositional Networks for Visual Captioning Zhe Gan, Chuang Gan, Xiaodong He, Yunchen Pu, Kenneth Tran, Jianfeng Gao, Lawrence Carin, Li Deng

ICML 2017 Stochastic Gradient Monomial Gamma Sampler Yizhe Zhang, Changyou Chen, Zhe Gan, Ricardo Henao, Lawrence Carin

NeurIPS 2017 Targeting EEG/LFP Synchrony with Neural Nets Yitong Li, Michael Murias, Samantha Major, Geraldine Dawson, Kafui Dzirasa, Lawrence Carin, David E Carlson

AISTATS 2017 Tensor-Dictionary Learning with Deep Kruskal-Factor Analysis Andrew Stevens, Yunchen Pu, Yannan Sun, Gregory Spell, Lawrence Carin

NeurIPS 2017 Triangle Generative Adversarial Networks Zhe Gan, Liqun Chen, Weiyao Wang, Yuchen Pu, Yizhe Zhang, Hao Liu, Chunyuan Li, Lawrence Carin

AAAI 2017 Unsupervised Learning with Truncated Gaussian Graphical Models Qinliang Su, Xuejun Liao, Chunyuan Li, Zhe Gan, Lawrence Carin

NeurIPS 2017 VAE Learning via Stein Variational Gradient Descent Yuchen Pu, Zhe Gan, Ricardo Henao, Chunyuan Li, Shaobo Han, Lawrence Carin

AISTATS 2016 A Deep Generative Deconvolutional Image Model Yunchen Pu, Xin Yuan, Andrew Stevens, Chunyuan Li, Lawrence Carin

IJCAI 2016 Bayesian Dictionary Learning with Gaussian Processes and Sigmoid Belief Networks Yizhe Zhang, Ricardo Henao, Chunyuan Li, Lawrence Carin

AISTATS 2016 Bridging the Gap Between Stochastic Gradient MCMC and Stochastic Optimization Changyou Chen, David E. Carlson, Zhe Gan, Chunyuan Li, Lawrence Carin

ECML-PKDD 2016 Deep Metric Learning with Data Summarization Wenlin Wang, Changyou Chen, Wenlin Chen, Piyush Rai, Lawrence Carin

JMLR 2016 Electronic Health Record Analysis via Deep Poisson Factor Models Ricardo Henao, James T. Lu, Joseph E. Lucas, Jeffrey Ferranti, Lawrence Carin

ICML 2016 Factored Temporal Sigmoid Belief Networks for Sequence Learning Jiaming Song, Zhe Gan, Lawrence Carin

AAAI 2016 High-Order Stochastic Gradient Thermostats for Bayesian Learning of Deep Models Chunyuan Li, Changyou Chen, Kai Fan, Lawrence Carin

ECML-PKDD 2016 Laplacian Hamiltonian Monte Carlo Yizhe Zhang, Changyou Chen, Ricardo Henao, Lawrence Carin

AISTATS 2016 Learning Sigmoid Belief Networks via Monte Carlo Expectation Maximization Zhao Song, Ricardo Henao, David E. Carlson, Lawrence Carin

CVPR 2016 Learning Weight Uncertainty with Stochastic Gradient MCMC for Shape Classification Chunyuan Li, Andrew Stevens, Changyou Chen, Yunchen Pu, Zhe Gan, Lawrence Carin

AAAI 2016 Learning a Hybrid Architecture for Sequence Regression and Annotation Yizhe Zhang, Ricardo Henao, Lawrence Carin, Jianling Zhong, Alexander J. Hartemink

NeurIPS 2016 Linear Feature Encoding for Reinforcement Learning Zhao Song, Ronald E Parr, Xuejun Liao, Lawrence Carin

AISTATS 2016 Non-Negative Matrix Factorization for Discrete Data with Hierarchical Side-Information Changwei Hu, Piyush Rai, Lawrence Carin

ICML 2016 Nonlinear Statistical Learning with Truncated Gaussian Graphical Models Qinliang Su, Xuejun Liao, Changyou Chen, Lawrence Carin

AISTATS 2016 Parallel Majorization Minimization with Dynamically Restricted Domains for Nonconvex Optimization Yan Kaganovsky, Ikenna Odinaka, David E. Carlson, Lawrence Carin

AAAI 2016 Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks Chunyuan Li, Changyou Chen, David E. Carlson, Lawrence Carin

NeurIPS 2016 Stochastic Gradient MCMC with Stale Gradients Changyou Chen, Nan Ding, Chunyuan Li, Yizhe Zhang, Lawrence Carin

AISTATS 2016 Topic-Based Embeddings for Learning from Large Knowledge Graphs Changwei Hu, Piyush Rai, Lawrence Carin

NeurIPS 2016 Towards Unifying Hamiltonian Monte Carlo and Slice Sampling Yizhe Zhang, Xiangyu Wang, Changyou Chen, Ricardo Henao, Kai Fan, Lawrence Carin

NeurIPS 2016 Variational Autoencoder for Deep Learning of Images, Labels and Captions Yunchen Pu, Zhe Gan, Ricardo Henao, Xin Yuan, Chunyuan Li, Andrew Stevens, Lawrence Carin

AISTATS 2016 Variational Gaussian Copula Inference Shaobo Han, Xuejun Liao, David B. Dunson, Lawrence Carin

ICLR 2015 A Generative Model for Deep Convolutional Learning Yunchen Pu, Xin Yuan, Lawrence Carin

ICML 2015 A Multitask Point Process Predictive Model Wenzhao Lian, Ricardo Henao, Vinayak Rao, Joseph Lucas, Lawrence Carin

AAAI 2015 Cross-Modal Similarity Learning via Pairs, Preferences, and Active Supervision Yi Zhen, Piyush Rai, Hongyuan Zha, Lawrence Carin

NeurIPS 2015 Deep Poisson Factor Modeling Ricardo Henao, Zhe Gan, James Lu, Lawrence Carin

NeurIPS 2015 Deep Temporal Sigmoid Belief Networks for Sequence Modeling Zhe Gan, Chunyuan Li, Ricardo Henao, David E Carlson, Lawrence Carin

NeurIPS 2015 GP Kernels for Cross-Spectrum Analysis Kyle R Ulrich, David E Carlson, Kafui Dzirasa, Lawrence Carin

AAAI 2015 Integrating Features and Similarities: Flexible Models for Heterogeneous Multiview Data Wenzhao Lian, Piyush Rai, Esther Salazar, Lawrence Carin

NeurIPS 2015 Large-Scale Bayesian Multi-Label Learning via Topic-Based Label Embeddings Piyush Rai, Changwei Hu, Ricardo Henao, Lawrence Carin

AISTATS 2015 Learning Deep Sigmoid Belief Networks with Data Augmentation Zhe Gan, Ricardo Henao, David E. Carlson, Lawrence Carin

AAAI 2015 Leveraging Features and Networks for Probabilistic Tensor Decomposition Piyush Rai, Yingjian Wang, Lawrence Carin

ICML 2015 Non-Gaussian Discriminative Factor Models via the Max-Margin Rank-Likelihood Xin Yuan, Ricardo Henao, Ephraim Tsalik, Raymond Langley, Lawrence Carin

NeurIPS 2015 On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators Changyou Chen, Nan Ding, Lawrence Carin

NeurIPS 2015 Preconditioned Spectral Descent for Deep Learning David E Carlson, Edo Collins, Ya-Ping Hsieh, Lawrence Carin, Volkan Cevher

ECML-PKDD 2015 Scalable Bayesian Non-Negative Tensor Factorization for Massive Count Data Changwei Hu, Piyush Rai, Changyou Chen, Matthew Harding, Lawrence Carin

ICML 2015 Scalable Deep Poisson Factor Analysis for Topic Modeling Zhe Gan, Changyou Chen, Ricardo Henao, David Carlson, Lawrence Carin

IJCAI 2015 Scalable Probabilistic Tensor Factorization for Binary and Count Data Piyush Rai, Changwei Hu, Matthew Harding, Lawrence Carin

IJCAI 2015 Stick-Breaking Policy Learning in Dec-POMDPs Miao Liu, Christopher Amato, Xuejun Liao, Lawrence Carin, Jonathan P. How

AISTATS 2015 Stochastic Spectral Descent for Restricted Boltzmann Machines David E. Carlson, Volkan Cevher, Lawrence Carin

UAI 2015 Zero-Truncated Poisson Tensor Factorization for Massive Binary Tensors Changwei Hu, Piyush Rai, Lawrence Carin

NeurIPS 2014 Analysis of Brain States from Multi-Region LFP Time-Series Kyle R Ulrich, David E Carlson, Wenzhao Lian, Jana S Borg, Kafui Dzirasa, Lawrence Carin

NeurIPS 2014 Bayesian Nonlinear Support Vector Machines and Discriminative Factor Modeling Ricardo Henao, Xin Yuan, Lawrence Carin

NeurIPS 2014 Compressive Sensing of Signals from a GMM with Sparse Precision Matrices Jianbo Yang, Xuejun Liao, Minhua Chen, Lawrence Carin

NeurIPS 2014 Dynamic Rank Factor Model for Text Streams Shaobo Han, Lin Du, Esther Salazar, Lawrence Carin

AISTATS 2014 Latent Gaussian Models for Topic Modeling Changwei Hu, Eunsu Ryu, David E. Carlson, Yingjian Wang, Lawrence Carin

CVPR 2014 Low-Cost Compressive Sensing for Color Video and Depth Xin Yuan, Patrick Llull, Xuejun Liao, Jianbo Yang, David J. Brady, Guillermo Sapiro, Lawrence Carin

ICML 2014 Modeling Correlated Arrival Events with Latent Semi-Markov Processes Wenzhao Lian, Vinayak Rao, Brian Eriksson, Lawrence Carin

CVPR 2014 Multi-Shot Imaging: Joint Alignment, Deblurring and Resolution-Enhancement Haichao Zhang, Lawrence Carin

ICML 2014 Nonlinear Information-Theoretic Compressive Measurement Design Liming Wang, Abolfazl Razi, Miguel Rodrigues, Robert Calderbank, Lawrence Carin

NeurIPS 2014 On the Relations of LFPs & Neural Spike Trains David E Carlson, Jana Schaich Borg, Kafui Dzirasa, Lawrence Carin

ICML 2014 Scalable Bayesian Low-Rank Decomposition of Incomplete Multiway Tensors Piyush Rai, Yingjian Wang, Shengbo Guo, Gary Chen, David Dunson, Lawrence Carin

NeurIPS 2013 Designed Measurements for Vector Count Data Liming Wang, David E Carlson, Miguel Rodrigues, David Wilcox, Robert Calderbank, Lawrence Carin

NeurIPS 2013 Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture Trevor Campbell, Miao Liu, Brian Kulis, Jonathan P How, Lawrence Carin

ICML 2013 Exploring the Mind: Integrating Questionnaires and fMRI Esther Salazar, Ryan Bogdan, Adam Gorka, Ahmad Hariri, Lawrence Carin

NeurIPS 2013 Integrated Non-Factorized Variational Inference Shaobo Han, Xuejun Liao, Lawrence Carin

IJCAI 2013 Online Expectation Maximization for Reinforcement Learning in POMDPs Miao Liu, Xuejun Liao, Lawrence Carin

NeurIPS 2013 Real-Time Inference for a Gamma Process Model of Neural Spiking David E Carlson, Vinayak Rao, Joshua T Vogelstein, Lawrence Carin

NeurIPS 2012 Augment-and-Conquer Negative Binomial Processes Mingyuan Zhou, Lawrence Carin

AISTATS 2012 Beta-Negative Binomial Process and Poisson Factor Analysis Mingyuan Zhou, Lauren Hannah, David Dunson, Lawrence Carin

ICML 2012 Communications Inspired Linear Discriminant Analysis Minhua Chen, William R. Carson, Miguel R. D. Rodrigues, Lawrence Carin, A. Robert Calderbank

ICML 2012 Cross-Domain Multitask Learning with Latent Probit Models Shaobo Han, Xuejun Liao, Lawrence Carin

ICML 2012 Inferring Latent Structure from Mixed Real and Categorical Relational Data Esther Salazar, Lawrence Carin

NeurIPS 2012 Joint Modeling of a Matrix with Associated Text via Latent Binary Features Xianxing Zhang, Lawrence Carin

ICML 2012 Levy Measure Decompositions for the Beta and Gamma Processes Yingjian Wang, Lawrence Carin

ICML 2012 Lognormal and Gamma Mixed Negative Binomial Regression Mingyuan Zhou, Lingbo Li, David B. Dunson, Lawrence Carin

UAI 2012 Nested Dictionary Learning for Hierarchical Organization of Imagery and Text Lingbo Li, XianXing Zhang, Mingyuan Zhou, Lawrence Carin

AISTATS 2011 Dependent Hierarchical Beta Process for Image Interpolation and Denoising Mingyuan Zhou, Hongxia Yang, Guillermo Sapiro, David Dunson, Lawrence Carin

NeurIPS 2011 Hierarchical Topic Modeling for Analysis of Time-Evolving Personal Choices Xianxing Zhang, Lawrence Carin, David B. Dunson

JMLR 2011 Logistic Stick-Breaking Process Lu Ren, Lan Du, Lawrence Carin, David Dunson

NeurIPS 2011 On the Analysis of Multi-Channel Neural Spike Data Bo Chen, David E. Carlson, Lawrence Carin

ICML 2011 On the Integration of Topic Modeling and Dictionary Learning Lingbo Li, Mingyuan Zhou, Guillermo Sapiro, Lawrence Carin

ICML 2011 The Hierarchical Beta Process for Convolutional Factor Analysis and Deep Learning Bo Chen, Gungor Polatkan, Guillermo Sapiro, David B. Dunson, Lawrence Carin

ICML 2011 The Infinite Regionalized Policy Representation Miao Liu, Xuejun Liao, Lawrence Carin

NeurIPS 2011 The Kernel Beta Process Lu Ren, Yingjian Wang, Lawrence Carin, David B. Dunson

ICML 2011 Topic Modeling with Nonparametric Markov Tree Haojun Chen, David B. Dunson, Lawrence Carin

ICML 2011 Tree-Structured Infinite Sparse Factor Model XianXing Zhang, David B. Dunson, Lawrence Carin

ICML 2011 Variational Inference for Stick-Breaking Beta Process Priors John W. Paisley, Lawrence Carin, David M. Blei

ICML 2010 A Stick-Breaking Construction of the Beta Process John W. Paisley, Aimee K. Zaas, Christopher W. Woods, Geoffrey S. Ginsburg, Lawrence Carin

JMLR 2010 Classification with Incomplete Data Using Dirichlet Process Priors Chunping Wang, Xuejun Liao, Lawrence Carin, David B. Dunson

NeurIPS 2010 Joint Analysis of Time-Evolving Binary Matrices and Associated Documents Eric Wang, Dehong Liu, Jorge Silva, Lawrence Carin, David B. Dunson

NeurIPS 2009 A Bayesian Model for Simultaneous Image Clustering, Annotation and Object Segmentation Lan Du, Lu Ren, Lawrence Carin, David B. Dunson

NeurIPS 2009 Learning to Explore and Exploit in POMDPs Chenghui Cai, Xuejun Liao, Lawrence Carin

JMLR 2009 Multi-Task Reinforcement Learning in Partially Observable Stochastic Environments Hui Li, Xuejun Liao, Lawrence Carin

NeurIPS 2009 Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations Mingyuan Zhou, Haojun Chen, Lu Ren, Guillermo Sapiro, Lawrence Carin, John W. Paisley

ICML 2009 Nonparametric Factor Analysis with Beta Process Priors John W. Paisley, Lawrence Carin

ICML 2008 Hierarchical Kernel Stick-Breaking Process for Multi-Task Image Analysis Qi An, Chunping Wang, Ivo Shterev, Eric Wang, Lawrence Carin, David B. Dunson

ICML 2008 Multi-Task Compressive Sensing with Dirichlet Process Priors Yuting Qi, Dehong Liu, David B. Dunson, Lawrence Carin

ICML 2008 The Dynamic Hierarchical Dirichlet Process Lu Ren, David B. Dunson, Lawrence Carin

ICML 2007 Bayesian Compressive Sensing and Projection Optimization Shihao Ji, Lawrence Carin

JMLR 2007 Multi-Task Learning for Classification with Dirichlet Process Priors Ya Xue, Xuejun Liao, Lawrence Carin, Balaji Krishnapuram

ICML 2007 Multi-Task Learning for Sequential Data via iHMMs and the Nested Dirichlet Process Kai Ni, Lawrence Carin, David B. Dunson

AAAI 2007 Point-Based Policy Iteration Shihao Ji, Ronald Parr, Hui Li, Xuejun Liao, Lawrence Carin

ICML 2007 Quadratically Gated Mixture of Experts for Incomplete Data Classification Xuejun Liao, Hui Li, Lawrence Carin

NeurIPS 2007 Semi-Supervised Multitask Learning Qiuhua Liu, Xuejun Liao, Lawrence Carin

ICML 2007 The Matrix Stick-Breaking Process for Flexible Multi-Task Learning Ya Xue, David B. Dunson, Lawrence Carin

AAAI 2006 Incremental Least Squares Policy Iteration for POMDPs Hui Li, Xuejun Liao, Lawrence Carin

ICML 2006 Region-Based Value Iteration for Partially Observable Markov Decision Processes Hui Li, Xuejun Liao, Lawrence Carin

CVPR 2005 A Bayesian Approach to Unsupervised Feature Selection and Density Estimation Using Expectation Propagation Shaorong Chang, Nilanjan Dasgupta, Lawrence Carin

ICML 2005 Incomplete-Data Classification Using Logistic Regression David Williams, Xuejun Liao, Ya Xue, Lawrence Carin

ICML 2005 Logistic Regression with an Auxiliary Data Source Xuejun Liao, Ya Xue, Lawrence Carin

NeurIPS 2005 Radial Basis Function Network for Multi-Task Learning Xuejun Liao, Lawrence Carin

NeurIPS 2004 On Semi-Supervised Classification Balaji Krishnapuram, David Williams, Ya Xue, Lawrence Carin, Mário Figueiredo, Alexander J. Hartemink