Deep Learning

Separating Signal from Noise Using Patch Recurrence across Scales CVPR 2013 Sharp Generalization Error Bounds for Randomly-projected Classifiers ICML 2013 Shufflets: Shared Mid-level Parts for Fast Object Detection ICCV 2013 Simple Sparsification Improves Sparse Denoising Autoencoders in Denoising Highly Corrupted Images ICML 2013 Sparse Activity and Sparse Connectivity in Supervised Learning JMLR 2013 Sparse Output Coding for Large-Scale Visual Recognition CVPR 2013 Sparse Quantization for Patch Description CVPR 2013 Sparsity-Based Generalization Bounds for Predictive Sparse Coding ICML 2013 Stochastic Gradient Riemannian Langevin Dynamics on the Probability Simplex NeurIPS 2013 Stochastic Optimization of PCA with Capped MSG NeurIPS 2013 Stochastic Ratio Matching of RBMs for Sparse High-Dimensional Inputs NeurIPS 2013 Stochastic Variational Inference JMLR 2013 Structural Expectation Propagation (SEP): Bayesian structure learning for networks with latent variables AISTATS 2013 Subspace Interpolation via Dictionary Learning for Unsupervised Domain Adaptation CVPR 2013 Supervised Sparse Analysis and Synthesis Operators NeurIPS 2013 Texture Enhanced Image Denoising via Gradient Histogram Preservation CVPR 2013 Texture Modeling with Convolutional Spike-and-Slab RBMs and Deep Extensions AISTATS 2013 The Episolar Constraint: Monocular Shape from Shadow Correspondence CVPR 2013 The Total Variation on Hypergraphs - Learning on Hypergraphs Revisited NeurIPS 2013 Top-Down Regularization of Deep Belief Networks NeurIPS 2013 Training and Analysing Deep Recurrent Neural Networks NeurIPS 2013 Translating Embeddings for Modeling Multi-relational Data NeurIPS 2013 Understanding Dropout NeurIPS 2013 Understanding High-Level Semantics by Modeling Traffic Patterns ICCV 2013 Unsupervised Joint Object Discovery and Segmentation in Internet Images CVPR 2013