Optimization & Theory

Full Flow: Optical Flow Estimation By Global Optimization Over Regular Grids CVPR 2016 Gaussian quadrature for matrix inverse forms with applications ICML 2016 Generalization Properties and Implicit Regularization for Multiple Passes SGM ICML 2016 Globally Optimal Training of Generalized Polynomial Neural Networks with Nonlinear Spectral Methods NeurIPS 2016 Gradient-Domain Image Reconstruction Framework With Intensity-Range and Base-Structure Constraints CVPR 2016 Gravitational Approach for Point Set Registration CVPR 2016 Group MAD Competition - A New Methodology to Compare Objective Image Quality Models CVPR 2016 HyperNet: Towards Accurate Region Proposal Generation and Joint Object Detection CVPR 2016 Improved Dropout for Shallow and Deep Learning NeurIPS 2016 Improving the Robustness of Deep Neural Networks via Stability Training CVPR 2016 Learning Deep Embeddings with Histogram Loss NeurIPS 2016 Learning Sensor Multiplexing Design through Back-propagation NeurIPS 2016 Learning Sparse High Dimensional Filters: Image Filtering, Dense CRFs and Bilateral Neural Networks CVPR 2016 Learning Structured Sparsity in Deep Neural Networks NeurIPS 2016 Learning the Number of Neurons in Deep Networks NeurIPS 2016 LightRNN: Memory and Computation-Efficient Recurrent Neural Networks NeurIPS 2016 Loss Functions for Top-k Error: Analysis and Insights CVPR 2016 Low-Rank Regression with Tensor Responses NeurIPS 2016 Maximal Sparsity with Deep Networks? NeurIPS 2016 Measuring the reliability of MCMC inference with bidirectional Monte Carlo NeurIPS 2016 Memory-Efficient Backpropagation Through Time NeurIPS 2016 Multispectral Images Denoising by Intrinsic Tensor Sparsity Regularization CVPR 2016 Network Morphism ICML 2016 Online PCA with Optimal Regret JMLR 2016 On the Efficient Representation and Execution of Deep Acoustic Models Interspeech 2016