representation learning

Deep AutoRegressive Networks ICML 2014 Discovering Structure in High-Dimensional Data Through Correlation Explanation NeurIPS 2014 Discriminative Unsupervised Feature Learning with Convolutional Neural Networks NeurIPS 2014 Do Deep Nets Really Need to be Deep? NeurIPS 2014 Expectation-Maximization for Learning Determinantal Point Processes NeurIPS 2014 Fast and Robust Archetypal Analysis for Representation Learning CVPR 2014 General Stochastic Networks for Classification NeurIPS 2014 How transferable are features in deep neural networks? NeurIPS 2014 Improved Multimodal Deep Learning with Variation of Information NeurIPS 2014 Latent Semantic Representation Learning for Scene Classification ICML 2014 Learning Mid-level Filters for Person Re-identification CVPR 2014 Learning Ordered Representations with Nested Dropout ICML 2014 Learning Sparsely Used Overcomplete Dictionaries COLT 2014 Marginalized Denoising Auto-encoders for Nonlinear Representations ICML 2014 Modeling Deep Temporal Dependencies with Recurrent Grammar Cells"" NeurIPS 2014 Neural Decision Forests for Semantic Image Labelling CVPR 2014 Pre-training of Recurrent Neural Networks via Linear Autoencoders NeurIPS 2014 Product Sparse Coding CVPR 2014 Provable Bounds for Learning Some Deep Representations ICML 2014 Scalable Multitask Representation Learning for Scene Classification CVPR 2014 Scalable Non-linear Learning with Adaptive Polynomial Expansions NeurIPS 2014 Sequence to Sequence Learning with Neural Networks NeurIPS 2014 Smooth Representation Clustering CVPR 2014 Stable and Efficient Representation Learning with Nonnegativity Constraints ICML 2014 Temporal Sequence Modeling for Video Event Detection CVPR 2014