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Neural Network Optimization

3,649 papers

Papers per year

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Papers

Learning to learn by gradient descent by gradient descent NIPS 2016
Optimal Learning for Multi-pass Stochastic Gradient Methods NIPS 2016
Natural-Parameter Networks: A Class of Probabilistic Neural Networks NIPS 2016
Towards Automatically-Tuned Neural Networks AUTOML 2016
Deep Gate Recurrent Neural Network ACML 2016
Accelerated Stochastic Gradient Descent for Minimizing Finite Sums AISTATS 2016
Towards Stability and Optimality in Stochastic Gradient Descent AISTATS 2016
Back to the Future: Radial Basis Function Networks Revisited AISTATS 2016
Interactive Attention for Neural Machine Translation COLING 2016
Textual Entailment with Structured Attentions and Composition COLING 2016
Neural Paraphrase Generation with Stacked Residual LSTM Networks COLING 2016
Measuring the Information Content of Financial News COLING 2016
benefits of depth in neural networks COLT 2016
How Far Are We From Solving Pedestrian Detection? CVPR 2016
Deeply-Recursive Convolutional Network for Image Super-Resolution CVPR 2016
Refining Architectures of Deep Convolutional Neural Networks CVPR 2016
Fast ConvNets Using Group-Wise Brain Damage CVPR 2016
Blockout: Dynamic Model Selection for Hierarchical Deep Networks CVPR 2016
Gradual DropIn of Layers to Train Very Deep Neural Networks CVPR 2016
Deep Speech 2 : End-to-End Speech Recognition in English and Mandarin ICML 2016
Stochastic Variance Reduction for Nonconvex Optimization ICML 2016
A Kronecker-factored approximate Fisher matrix for convolution layers ICML 2016
Hyperparameter optimization with approximate gradient ICML 2016
On the Quality of the Initial Basin in Overspecified Neural Networks ICML 2016
Improved SVRG for Non-Strongly-Convex or Sum-of-Non-Convex Objectives ICML 2016