Representation Learning

Information Bottleneck Optimization and Independent Component Extraction with Spiking Neurons NeurIPS 2006 In-Network PCA and Anomaly Detection NeurIPS 2006 In Search of Non-Gaussian Components of a High-Dimensional Distribution JMLR 2006 Kernel Maximum Entropy Data Transformation and an Enhanced Spectral Clustering Algorithm NeurIPS 2006 Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting JMLR 2006 Kernels on Structured Objects Through Nested Histograms NeurIPS 2006 Large Margin Component Analysis NeurIPS 2006 Large Scale Multiple Kernel Learning JMLR 2006 Large-Scale Sparsified Manifold Regularization NeurIPS 2006 Learning annotated hierarchies from relational data NeurIPS 2006 Learning Coordinate Covariances via Gradients JMLR 2006 Learning Dense 3D Correspondence NeurIPS 2006 Learning Image Components for Object Recognition JMLR 2006 Learning on Graph with Laplacian Regularization NeurIPS 2006 Learning Parts-Based Representations of Data JMLR 2006 Learning Sparse Representations by Non-Negative Matrix Factorization and Sequential Cone Programming JMLR 2006 Learning to parse images of articulated bodies NeurIPS 2006 Learning to Traverse Image Manifolds NeurIPS 2006 Learning with Hypergraphs: Clustering, Classification, and Embedding NeurIPS 2006 Linear State-Space Models for Blind Source Separation JMLR 2006 Lower Bounds and Aggregation in Density Estimation JMLR 2006 MinReg: A Scalable Algorithm for Learning Parsimonious Regulatory Networks in Yeast and Mammals JMLR 2006 MLLE: Modified Locally Linear Embedding Using Multiple Weights NeurIPS 2006 Modeling Dyadic Data with Binary Latent Factors NeurIPS 2006 Modeling General and Specific Aspects of Documents with a Probabilistic Topic Model NeurIPS 2006