Representation Learning

Modeling Human Motion Using Binary Latent Variables NeurIPS 2006 Multi-Task Feature Learning NeurIPS 2006 Nonnegative Sparse PCA NeurIPS 2006 Particle Filtering for Nonparametric Bayesian Matrix Factorization NeurIPS 2006 Quantile Regression Forests JMLR 2006 Randomized PCA Algorithms with Regret Bounds that are Logarithmic in the Dimension NeurIPS 2006 Recursive Attribute Factoring NeurIPS 2006 Recursive ICA NeurIPS 2006 Relational Learning with Gaussian Processes NeurIPS 2006 Sparse Kernel Orthonormalized PLS for feature extraction in large data sets NeurIPS 2006 Sparse Representation for Signal Classification NeurIPS 2006 Stratification Learning: Detecting Mixed Density and Dimensionality in High Dimensional Point Clouds NeurIPS 2006 Streamwise Feature Selection JMLR 2006 Temporal and Cross-Subject Probabilistic Models for fMRI Prediction Tasks NeurIPS 2006 Temporal Coding using the Response Properties of Spiking Neurons NeurIPS 2006 Towards a general independent subspace analysis NeurIPS 2006 Universal Kernels JMLR 2006 Unsupervised Regression with Applications to Nonlinear System Identification NeurIPS 2006 Diffusion Kernels on Statistical Manifolds JMLR 2005 Feature Selection for Unsupervised and Supervised Inference: The Emergence of Sparsity in a Weight-Based Approach JMLR 2005 Information Bottleneck for Gaussian Variables JMLR 2005 Learning Hidden Variable Networks: The Information Bottleneck Approach JMLR 2005 Learning Module Networks JMLR 2005 Learning Multiple Tasks with Kernel Methods JMLR 2005 Multiclass Classification with Multi-Prototype Support Vector Machines JMLR 2005