Representation Learning

Probabilistic Non-linear Principal Component Analysis with Gaussian Process Latent Variable Models JMLR 2005 Semigroup Kernels on Measures JMLR 2005 A Fast Algorithm for Joint Diagonalization with Non-orthogonal Transformations and its Application to Blind Source Separation JMLR 2004 Non-negative Matrix Factorization with Sparseness Constraints JMLR 2004 Reinforcement Learning with Factored States and Actions JMLR 2004 Weather Data Mining Using Independent Component Analysis JMLR 2004 A General Framework for Distributional Similarity EMNLP 2003 A Neural Probabilistic Language Model JMLR 2003 An Introduction to Variable and Feature Selection JMLR 2003 Beyond Independent Components: Trees and Clusters JMLR 2003 Blind Source Separation via Generalized Eigenvalue Decomposition JMLR 2003 Energy-Based Models for Sparse Overcomplete Representations JMLR 2003 Extensions to Metric-Based Model Selection JMLR 2003 Feature Extraction by Non-Parametric Mutual Information Maximization JMLR 2003 Fusion of Domain Knowledge with Data for Structural Learning in Object Oriented Domains JMLR 2003 ICA Using Spacings Estimates of Entropy JMLR 2003 Inducing Grammars from Sparse Data Sets: A Survey of Algorithms and Results JMLR 2003 Least-Squares Policy Iteration JMLR 2003 MISEP -- Linear and Nonlinear ICA Based on Mutual Information JMLR 2003 Overlearning in Marginal Distribution-Based ICA: Analysis and Solutions JMLR 2003 Statistical Dynamics of On-line Independent Component Analysis JMLR 2003 Sufficient Dimensionality Reduction JMLR 2003 The Principled Design of Large-Scale Recursive Neural Network Architectures--DAG-RNNs and the Protein Structure Prediction Problem JMLR 2003 Think Globally, Fit Locally: Unsupervised Learning of Low Dimensional Manifolds JMLR 2003 Kernel Independent Component Analysis JMLR 2002