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Neural Network Optimization

3,649 papers

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Papers

Parallelized Stochastic Gradient Descent NIPS 2010
Understanding the difficulty of training deep feedforward neural networks AISTATS 2010
Erratum: SGDQN is Less Careful than Expected JMLR 2010
Convergent Temporal-Difference Learning with Arbitrary Smooth Function Approximation NIPS 2009
Efficient Learning using Forward-Backward Splitting NIPS 2009
Periodic Step Size Adaptation for Single Pass On-line Learning NIPS 2009
A Generalized Natural Actor-Critic Algorithm NIPS 2009
A Smoothed Approximate Linear Program NIPS 2009
Accelerated Gradient Methods for Stochastic Optimization and Online Learning NIPS 2009
SGD-QN: Careful Quasi-Newton Stochastic Gradient Descent JMLR 2009
Deep Learning with Kernel Regularization for Visual Recognition NIPS 2008
Topmoumoute Online Natural Gradient Algorithm NIPS 2007
One-Pass Boosting NIPS 2007
On higher-order perceptron algorithms NIPS 2007
Learning to classify complex patterns using a VLSI network of spiking neurons NIPS 2007
Nonlinear Boosting Projections for Ensemble Construction JMLR 2007
Noise Tolerant Variants of the Perceptron Algorithm JMLR 2007
Greedy Layer-Wise Training of Deep Networks NIPS 2006
An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM Models NIPS 2006
A Very Fast Learning Method for Neural Networks Based on Sensitivity Analysis JMLR 2006
A Modified Finite Newton Method for Fast Solution of Large Scale Linear SVMs JMLR 2005
Quasi-Geodesic Neural Learning Algorithms Over the Orthogonal Group: A Tutorial JMLR 2005
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