NIPS Proceedingsβ

Lawrence Carin

27 Papers

  • Deep Poisson Factor Modeling (2015)
  • Deep Temporal Sigmoid Belief Networks for Sequence Modeling (2015)
  • GP Kernels for Cross-Spectrum Analysis (2015)
  • Large-Scale Bayesian Multi-Label Learning via Topic-Based Label Embeddings (2015)
  • On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators (2015)
  • Preconditioned Spectral Descent for Deep Learning (2015)
  • Analysis of Brain States from Multi-Region LFP Time-Series (2014)
  • Bayesian Nonlinear Support Vector Machines and Discriminative Factor Modeling (2014)
  • Compressive Sensing of Signals from a GMM with Sparse Precision Matrices (2014)
  • Dynamic Rank Factor Model for Text Streams (2014)
  • On the relations of LFPs & Neural Spike Trains (2014)
  • Designed Measurements for Vector Count Data (2013)
  • Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture (2013)
  • Integrated Non-Factorized Variational Inference (2013)
  • Real-Time Inference for a Gamma Process Model of Neural Spiking (2013)
  • Augment-and-Conquer Negative Binomial Processes (2012)
  • Joint Modeling of a Matrix with Associated Text via Latent Binary Features (2012)
  • Hierarchical Topic Modeling for Analysis of Time-Evolving Personal Choices (2011)
  • On the Analysis of Multi-Channel Neural Spike Data (2011)
  • The Kernel Beta Process (2011)
  • Joint Analysis of Time-Evolving Binary Matrices and Associated Documents (2010)
  • A Bayesian Model for Simultaneous Image Clustering, Annotation and Object Segmentation (2009)
  • Learning to Explore and Exploit in POMDPs (2009)
  • Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations (2009)
  • Semi-Supervised Multitask Learning (2007)
  • Radial Basis Function Network for Multi-task Learning (2005)
  • On Semi-Supervised Classification (2004)