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Neural Network Optimization

3648 directly classified papers

Papers per year

Papers

Static Automatic Batching In TensorFlow ICML 2019
RecurJac: An Efficient Recursive Algorithm for Bounding Jacobian Matrix of Neural Networks and Its Applications AAAI 2019
Quantity doesn’t buy quality syntax with neural language models IJCNLP 2019
Momentum-Based Variance Reduction in Non-Convex SGD NIPS 2019
On NMT Search Errors and Model Errors: Cat Got Your Tongue? IJCNLP 2019
Attention Optimization for Abstractive Document Summarization IJCNLP 2019
Surrogate Losses for Online Learning of Stepsizes in Stochastic Non-Convex Optimization ICML 2019
Differentiable Linearized ADMM ICML 2019
Overparameterized Nonlinear Learning: Gradient Descent Takes the Shortest Path? ICML 2019
AdaGrad Stepsizes: Sharp Convergence Over Nonconvex Landscapes ICML 2019
Differentiable Kernel Evolution ICCV 2019
Efficient Learning of Restricted Boltzmann Machines Using Covariance Estimates ACML 2019
One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers NIPS 2019
EvalNorm: Estimating Batch Normalization Statistics for Evaluation ICCV 2019
On Dropout and Nuclear Norm Regularization ICML 2019
DBDNet: Learning Bi-directional Dynamics for Early Action Prediction IJCAI 2019
SGD: General Analysis and Improved Rates ICML 2019
SAGA with Arbitrary Sampling ICML 2019
A Dynamical Systems Perspective on Nesterov Acceleration ICML 2019
On Model Stability as a Function of Random Seed CONLL 2019
Cubic Regularization with Momentum for Nonconvex Optimization UAI 2019
NAS-Bench-101: Towards Reproducible Neural Architecture Search ICML 2019
RNN Architecture Learning with Sparse Regularization IJCNLP 2019
Simple Stochastic Gradient Methods for Non-Smooth Non-Convex Regularized Optimization ICML 2019
Low-Rank HOCA: Efficient High-Order Cross-Modal Attention for Video Captioning IJCNLP 2019