Optimization & Theory

A Stochastic PCA and SVD Algorithm with an Exponential Convergence Rate ICML 2015 Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization NeurIPS 2015 Backpropagation for Energy-Efficient Neuromorphic Computing NeurIPS 2015 BinaryConnect: Training Deep Neural Networks with binary weights during propagations NeurIPS 2015 Computationally Bounded Retrieval CVPR 2015 Convolutional Neural Networks at Constrained Time Cost CVPR 2015 Deep learning with Elastic Averaging SGD NeurIPS 2015 Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification ICCV 2015 Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse Targets NeurIPS 2015 \ell_1,p-Norm Regularization: Error Bounds and Convergence Rate Analysis of First-Order Methods ICML 2015 Equilibrated adaptive learning rates for non-convex optimization NeurIPS 2015 Escaping From Saddle Points — Online Stochastic Gradient for Tensor Decomposition COLT 2015 FaLRR: A Fast Low Rank Representation Solver CVPR 2015 Fast and Guaranteed Tensor Decomposition via Sketching NeurIPS 2015 Fast Randomized Singular Value Thresholding for Nuclear Norm Minimization CVPR 2015 Frequency-Based Environment Matting by Compressive Sensing ICCV 2015 Gradient Estimation Using Stochastic Computation Graphs NeurIPS 2015 Hessian-free Optimization for Learning Deep Multidimensional Recurrent Neural Networks NeurIPS 2015 Improved Iteration Complexity Bounds of Cyclic Block Coordinate Descent for Convex Problems NeurIPS 2015 Improving Object Proposals With Multi-Thresholding Straddling Expansion CVPR 2015 Learning both Weights and Connections for Efficient Neural Network NeurIPS 2015 Learning with a Wasserstein Loss NeurIPS 2015 Learning with Incremental Iterative Regularization NeurIPS 2015 Less is More: Nyström Computational Regularization NeurIPS 2015 Low-Rank Tensor Approximation With Laplacian Scale Mixture Modeling for Multiframe Image Denoising ICCV 2015