Deep Learning

A Stochastic Gradient Method with an Exponential Convergence _Rate for Finite Training Sets NeurIPS 2012 Bayesian Probabilistic Co-Subspace Addition NeurIPS 2012 Bayesian Warped Gaussian Processes NeurIPS 2012 Calibrated Elastic Regularization in Matrix Completion NeurIPS 2012 Cardinality Restricted Boltzmann Machines NeurIPS 2012 Classification Calibration Dimension for General Multiclass Losses NeurIPS 2012 Clustering by Nonnegative Matrix Factorization Using Graph Random Walk NeurIPS 2012 Cocktail Party Processing via Structured Prediction NeurIPS 2012 Compressive neural representation of sparse, high-dimensional probabilities NeurIPS 2012 Convolutional-Recursive Deep Learning for 3D Object Classification NeurIPS 2012 Cumulative Restricted Boltzmann Machines for Ordinal Matrix Data Analysis ACML 2012 Deep Boltzmann Machines as Feed-Forward Hierarchies AISTATS 2012 Deep Learning Made Easier by Linear Transformations in Perceptrons AISTATS 2012 Deep Learning of Invariant Features via Simulated Fixations in Video NeurIPS 2012 Deep Neural Networks Segment Neuronal Membranes in Electron Microscopy Images NeurIPS 2012 Deep Representations and Codes for Image Auto-Annotation NeurIPS 2012 Deep Spatio-Temporal Architectures and Learning for Protein Structure Prediction NeurIPS 2012 Delay Compensation with Dynamical Synapses NeurIPS 2012 Dip-means: an incremental clustering method for estimating the number of clusters NeurIPS 2012 Discriminative Learning of Sum-Product Networks NeurIPS 2012 Distributed Probabilistic Learning for Camera Networks with Missing Data NeurIPS 2012 Dynamical And-Or Graph Learning for Object Shape Modeling and Detection NeurIPS 2012 Efficient and direct estimation of a neural subunit model for sensory coding NeurIPS 2012 Efficient Monte Carlo Counterfactual Regret Minimization in Games with Many Player Actions NeurIPS 2012 Efficient Spike-Coding with Multiplicative Adaptation in a Spike Response Model NeurIPS 2012