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Neural Network Optimization

3648 directly classified papers

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Papers

Model Accuracy and Runtime Tradeoff in Distributed Deep Learning: A Systematic Study IJCAI 2017
To Improve the Robustness of LSTM-RNN Acoustic Models Using Higher-Order Feedback from Multiple Histories INTERSPEECH 2017
Accelerating Stochastic Composition Optimization JMLR 2017
Less than a Single Pass: Stochastically Controlled Stochastic Gradient AISTATS 2017
Stochastic Gradient Descent as Approximate Bayesian Inference JMLR 2017
DrMAD: Distilling Reverse-Mode Automatic Differentiation for Optimizing Hyperparameters of Deep Neural Networks IJCAI 2016
Fast ConvNets Using Group-Wise Brain Damage CVPR 2016
Recurrent Orthogonal Networks and Long-Memory Tasks ICML 2016
Starting Small - Learning with Adaptive Sample Sizes ICML 2016
Full-Capacity Unitary Recurrent Neural Networks NIPS 2016
Generalization Properties and Implicit Regularization for Multiple Passes SGM ICML 2016
A Multi-Batch L-BFGS Method for Machine Learning NIPS 2016
Energetic Natural Gradient Descent ICML 2016
Persistent RNNs: Stashing Recurrent Weights On-Chip ICML 2016
A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights JMLR 2016
On Lower and Upper Bounds in Smooth and Strongly Convex Optimization JMLR 2016
Strongly-Typed Recurrent Neural Networks ICML 2016
Deep Gate Recurrent Neural Network ACML 2016
benefits of depth in neural networks COLT 2016
Towards Stability and Optimality in Stochastic Gradient Descent AISTATS 2016
On the Quality of the Initial Basin in Overspecified Neural Networks ICML 2016
Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameters ICML 2016
Interactive Attention for Neural Machine Translation COLING 2016
Textual Entailment with Structured Attentions and Composition COLING 2016
Residual Networks Behave Like Ensembles of Relatively Shallow Networks NIPS 2016