Deep Learning

Emergence of Object-Selective Features in Unsupervised Feature Learning NeurIPS 2012 Exact and Stable Recovery of Sequences of Signals with Sparse Increments via Differential _1-Minimization NeurIPS 2012 Fast Bayesian Inference for Non-Conjugate Gaussian Process Regression NeurIPS 2012 Feature Clustering for Accelerating Parallel Coordinate Descent NeurIPS 2012 Fused sparsity and robust estimation for linear models with unknown variance NeurIPS 2012 Fusion with Diffusion for Robust Visual Tracking NeurIPS 2012 Generalization Bounds for Domain Adaptation NeurIPS 2012 Hierarchical Latent Dictionaries for Models of Brain Activation AISTATS 2012 Hierarchical spike coding of sound NeurIPS 2012 Homeostatic plasticity in Bayesian spiking networks as Expectation Maximization with posterior constraints NeurIPS 2012 Image Denoising and Inpainting with Deep Neural Networks NeurIPS 2012 ImageNet Classification with Deep Convolutional Neural Networks NeurIPS 2012 Imitation Learning by Coaching NeurIPS 2012 Isotropic Hashing NeurIPS 2012 Krylov Subspace Descent for Deep Learning AISTATS 2012 Large Scale Distributed Deep Networks NeurIPS 2012 Learned Prioritization for Trading Off Accuracy and Speed NeurIPS 2012 Learning Algorithms for the Classification Restricted Boltzmann Machine JMLR 2012 Learning as MAP Inference in Discrete Graphical Models NeurIPS 2012 Learning curves for multi-task Gaussian process regression NeurIPS 2012 Learning Image Descriptors with the Boosting-Trick NeurIPS 2012 Learning Invariant Representations of Molecules for Atomization Energy Prediction NeurIPS 2012 Learning optimal spike-based representations NeurIPS 2012 Learning the Architecture of Sum-Product Networks Using Clustering on Variables NeurIPS 2012 Learning to Align from Scratch NeurIPS 2012