Deep Learning

Online Optimization for Max-Norm Regularization NeurIPS 2014 On Model Parallelization and Scheduling Strategies for Distributed Machine Learning NeurIPS 2014 On Multiplicative Multitask Feature Learning NeurIPS 2014 On the Computational Efficiency of Training Neural Networks NeurIPS 2014 On the Number of Linear Regions of Deep Neural Networks NeurIPS 2014 Optimizing F-Measures by Cost-Sensitive Classification NeurIPS 2014 Orbit Regularization NeurIPS 2014 PANDA: Pose Aligned Networks for Deep Attribute Modeling CVPR 2014 Parallel Double Greedy Submodular Maximization NeurIPS 2014 Patch to the Future: Unsupervised Visual Prediction CVPR 2014 Predicting Matchability CVPR 2014 Preserving Modes and Messages via Diverse Particle Selection ICML 2014 Pre-training of Recurrent Neural Networks via Linear Autoencoders NeurIPS 2014 Projective dictionary pair learning for pattern classification NeurIPS 2014 Provable Bounds for Learning Some Deep Representations ICML 2014 Proximal Quasi-Newton for Computationally Intensive L1-regularized M-estimators NeurIPS 2014 Pulling Things out of Perspective CVPR 2014 Quasi Real-Time Summarization for Consumer Videos CVPR 2014 QUIC & DIRTY: A Quadratic Approximation Approach for Dirty Statistical Models NeurIPS 2014 Randomized Nonlinear Component Analysis ICML 2014 Recognizing RGB Images by Learning from RGB-D Data CVPR 2014 Recovering Surface Details under General Unknown Illumination Using Shading and Coarse Multi-view Stereo CVPR 2014 Recurrent Convolutional Neural Networks for Scene Labeling ICML 2014 Recurrent Models of Visual Attention NeurIPS 2014 Recursive Context Propagation Network for Semantic Scene Labeling NeurIPS 2014