Representation Learning

Supervised Topic Models NeurIPS 2007 The Infinite Gamma-Poisson Feature Model NeurIPS 2007 Undercomplete Blind Subspace Deconvolution JMLR 2007 Accurate Error Bounds for the Eigenvalues of the Kernel Matrix JMLR 2006 A Graphical Representation of Equivalence Classes of AMP Chain Graphs JMLR 2006 A Kernel Subspace Method by Stochastic Realization for Learning Nonlinear Dynamical Systems NeurIPS 2006 Analysis of Representations for Domain Adaptation NeurIPS 2006 A Scoring Function for Learning Bayesian Networks based on Mutual Information and Conditional Independence Tests JMLR 2006 Bayesian Model Scoring in Markov Random Fields NeurIPS 2006 Blind source separation for over-determined delayed mixtures NeurIPS 2006 Conditional mean field NeurIPS 2006 Convergence of Laplacian Eigenmaps NeurIPS 2006 Denoising and Dimension Reduction in Feature Space NeurIPS 2006 Efficient Learning of Sparse Representations with an Energy-Based Model NeurIPS 2006 Efficient sparse coding algorithms NeurIPS 2006 Efficient Structure Learning of Markov Networks using L_1-Regularization NeurIPS 2006 Emergence of conjunctive visual features by quadratic independent component analysis NeurIPS 2006 Fast Iterative Kernel PCA NeurIPS 2006 Gaussian and Wishart Hyperkernels NeurIPS 2006 Generalized Maximum Margin Clustering and Unsupervised Kernel Learning NeurIPS 2006 Graph Laplacian Regularization for Large-Scale Semidefinite Programming NeurIPS 2006 High-Dimensional Graphical Model Selection Using ℓ_1-Regularized Logistic Regression NeurIPS 2006 implicit Online Learning with Kernels NeurIPS 2006 Inferring Network Structure from Co-Occurrences NeurIPS 2006 Information Bottleneck for Non Co-Occurrence Data NeurIPS 2006