gradient descent

Accelerating Stochastic Gradient Descent using Predictive Variance Reduction NeurIPS 2013 Algorithms and Hardness Results for Parallel Large Margin Learning JMLR 2013 Alternating Decision Forests CVPR 2013 Dimension-Free Exponentiated Gradient NeurIPS 2013 Linear Convergence with Condition Number Independent Access of Full Gradients NeurIPS 2013 On autoencoder scoring ICML 2013 On Decomposing the Proximal Map NeurIPS 2013 On the difficulty of training recurrent neural networks ICML 2013 Pregrasp Manipulation as Trajectory Optimization RSS 2013 Regularization-Free Principal Curve Estimation JMLR 2013 Stochastic Optimization of PCA with Capped MSG NeurIPS 2013 Deep Learning Made Easier by Linear Transformations in Perceptrons AISTATS 2012 Generic Methods for Optimization-Based Modeling AISTATS 2012 Gradient-based kernel method for feature extraction and variable selection NeurIPS 2012 Online Optimization with Gradual Variations COLT 2012 Optimal Distributed Online Prediction Using Mini-Batches JMLR 2012 Scaled Gradients on Grassmann Manifolds for Matrix Completion NeurIPS 2012 Better Mini-Batch Algorithms via Accelerated Gradient Methods NeurIPS 2011 Beyond the regret minimization barrier: an optimal algorithm for stochastic strongly-convex optimization COLT 2011 Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization NeurIPS 2011 Distributed Delayed Stochastic Optimization NeurIPS 2011 Efficient Methods for Overlapping Group Lasso NeurIPS 2011 Minimax Policies for Combinatorial Prediction Games COLT 2011 Multiclass Boosting: Theory and Algorithms NeurIPS 2011 Regression on Fixed-Rank Positive Semidefinite Matrices: A Riemannian Approach JMLR 2011