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Neural Network Optimization

3648 directly classified papers

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Papers

What Part of the Neural Network Does This? Understanding LSTMs by Measuring and Dissecting Neurons IJCNLP 2019
Optimization of Inf-Convolution Regularized Nonconvex Composite Problems AISTATS 2019
Parallelizable Stack Long Short-Term Memory NAACL 2019
Spatiotemporal Multi-Graph Convolution Network for Ride-Hailing Demand Forecasting AAAI 2019
CircConv: A Structured Convolution with Low Complexity AAAI 2019
The Lower The Simpler: Simplifying Hierarchical Recurrent Models NAACL 2019
Dynamical Isometry is Achieved in Residual Networks in a Universal Way for any Activation Function AISTATS 2019
Learning One-hidden-layer Neural Networks under General Input Distributions AISTATS 2019
Learning One-hidden-layer ReLU Networks via Gradient Descent AISTATS 2019
GIRNet: Interleaved Multi-Task Recurrent State Sequence Models AAAI 2019
Searching for a Robust Neural Architecture in Four GPU Hours CVPR 2019
New Convergence Aspects of Stochastic Gradient Algorithms JMLR 2019
Data-Driven Neuron Allocation for Scale Aggregation Networks CVPR 2019
Customizable Architecture Search for Semantic Segmentation CVPR 2019
Breaking Inter-Layer Co-Adaptation by Classifier Anonymization ICML 2019
Normal Approximation for Stochastic Gradient Descent via Non-Asymptotic Rates of Martingale CLT COLT 2019
Sharp Analysis for Nonconvex SGD Escaping from Saddle Points COLT 2019
Towards Non-Saturating Recurrent Units for Modelling Long-Term Dependencies AAAI 2019
Stabilized SVRG: Simple Variance Reduction for Nonconvex Optimization COLT 2019
On the Dynamics of Gradient Descent for Autoencoders AISTATS 2019
Distribution-Dependent Analysis of Gibbs-ERM Principle COLT 2019
Lipschitz Adaptivity with Multiple Learning Rates in Online Learning COLT 2019
Improving Deep Transformer with Depth-Scaled Initialization and Merged Attention IJCNLP 2019
Guided Dropout AAAI 2019
Faster Distributed Deep Net Training: Computation and Communication Decoupled Stochastic Gradient Descent IJCAI 2019