gradient descent

Statistical Tests for Optimization Efficiency NeurIPS 2011 An analysis on negative curvature induced by singularity in multi-layer neural-network learning NeurIPS 2010 Direct Loss Minimization for Structured Prediction NeurIPS 2010 Understanding the difficulty of training deep feedforward neural networks AISTATS 2010 Analysis of SVM with Indefinite Kernels NeurIPS 2009 Efficient Large-Scale Distributed Training of Conditional Maximum Entropy Models NeurIPS 2009 Efficient Learning using Forward-Backward Splitting NeurIPS 2009 Heavy-Tailed Symmetric Stochastic Neighbor Embedding NeurIPS 2009 Learning Non-Linear Combinations of Kernels NeurIPS 2009 On Learning Rotations NeurIPS 2009 ICA based on a Smooth Estimation of the Differential Entropy NeurIPS 2008 Mind the Duality Gap: Logarithmic regret algorithms for online optimization NeurIPS 2008 Adaptive Online Gradient Descent NeurIPS 2007 An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM Models NeurIPS 2006 Large Margin Multi-channel Analog-to-Digital Conversion with Applications to Neural Prosthesis NeurIPS 2006 Online Clustering of Moving Hyperplanes NeurIPS 2006 Sparse Boosting JMLR 2006 Smooth ε-Insensitive Regression by Loss Symmetrization JMLR 2005 Grafting: Fast, Incremental Feature Selection by Gradient Descent in Function Space JMLR 2003 The Principled Design of Large-Scale Recursive Neural Network Architectures--DAG-RNNs and the Protein Structure Prediction Problem JMLR 2003 Prior Knowledge and Preferential Structures in Gradient Descent Learning Algorithms JMLR 2001