Neural Network Optimization

Solving Random Systems of Quadratic Equations via Truncated Generalized Gradient Flow NeurIPS 2016 Backpropagation for Energy-Efficient Neuromorphic Computing NeurIPS 2015 BinaryConnect: Training Deep Neural Networks with binary weights during propagations NeurIPS 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 Natural Neural Networks NeurIPS 2015 Path-SGD: Path-Normalized Optimization in Deep Neural Networks NeurIPS 2015 Preconditioned Spectral Descent for Deep Learning NeurIPS 2015 Spectral Representations for Convolutional Neural Networks NeurIPS 2015 Training Very Deep Networks NeurIPS 2015 Variance Reduced Stochastic Gradient Descent with Neighbors NeurIPS 2015 An Accelerated Proximal Coordinate Gradient Method NeurIPS 2014 Identifying and attacking the saddle point problem in high-dimensional non-convex optimization NeurIPS 2014 Accelerating Stochastic Gradient Descent using Predictive Variance Reduction NeurIPS 2013 A General Iterative Shrinkage and Thresholding Algorithm for Non-convex Regularized Optimization Problems ICML 2013 Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n) NeurIPS 2013 Predicting Parameters in Deep Learning NeurIPS 2013 Understanding Dropout NeurIPS 2013 Deep Learning Made Easier by Linear Transformations in Perceptrons AISTATS 2012 Learning optimal spike-based representations NeurIPS 2012 Stochastic Gradient Descent with Only One Projection NeurIPS 2012 Algorithms for Hyper-Parameter Optimization NeurIPS 2011