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Neural Network Optimization

3648 directly classified papers

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Papers

Convergence Analysis of Gradient Descent for Eigenvector Computation IJCAI 2018
Refine or Represent: Residual Networks with Explicit Channel-wise Configuration IJCAI 2018
Stochastic Second-Order Method for Large-Scale Nonconvex Sparse Learning Models IJCAI 2018
The Context-Dependent Additive Recurrent Neural Net NAACL 2018
Dense Information Flow for Neural Machine Translation NAACL 2018
Lyapunov Functions for First-Order Methods: Tight Automated Convergence Guarantees ICML 2018
Stochastic Variance-Reduced Cubic Regularized Newton Methods ICML 2018
On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization ICML 2018
Comparing Dynamics: Deep Neural Networks versus Glassy Systems ICML 2018
signSGD: Compressed Optimisation for Non-Convex Problems ICML 2018
A Progressive Batching L-BFGS Method for Machine Learning ICML 2018
Dynamical Isometry and a Mean Field Theory of RNNs: Gating Enables Signal Propagation in Recurrent Neural Networks ICML 2018
Orthogonal Recurrent Neural Networks with Scaled Cayley Transform ICML 2018
On the Implicit Bias of Dropout ICML 2018
Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization ICML 2018
Learning Long Term Dependencies via Fourier Recurrent Units ICML 2018
Optimization based Layer-wise Magnitude-based Pruning for DNN Compression IJCAI 2018
Escaping Saddles with Stochastic Gradients ICML 2018
Experienced Optimization with Reusable Directional Model for Hyper-Parameter Search IJCAI 2018
Neural Ranking Models for Temporal Dependency Structure Parsing EMNLP 2018
PiCANet: Learning Pixel-Wise Contextual Attention for Saliency Detection CVPR 2018
A PID Controller Approach for Stochastic Optimization of Deep Networks CVPR 2018
Progressive Blockwise Knowledge Distillation for Neural Network Acceleration IJCAI 2018
Scale-Recurrent Network for Deep Image Deblurring CVPR 2018
MorphNet: Fast & Simple Resource-Constrained Structure Learning of Deep Networks CVPR 2018