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Neural Network Optimization

3,649 papers

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Papers

The Lottery Ticket Hypothesis for Pre-trained BERT Networks NIPS 2020
Explicit Regularisation in Gaussian Noise Injections NIPS 2020
Interpolation Technique to Speed Up Gradients Propagation in Neural ODEs NIPS 2020
Conformal Symplectic and Relativistic Optimization NIPS 2020
The Surprising Simplicity of the Early-Time Learning Dynamics of Neural Networks NIPS 2020
Directional convergence and alignment in deep learning NIPS 2020
Random Reshuffling: Simple Analysis with Vast Improvements NIPS 2020
Unfolding recurrence by Green’s functions for optimized reservoir computing NIPS 2020
A Finite-Time Analysis of Two Time-Scale Actor-Critic Methods NIPS 2020
Learning to Mutate with Hypergradient Guided Population NIPS 2020
Robust Recovery via Implicit Bias of Discrepant Learning Rates for Double Over-parameterization NIPS 2020
Bayesian filtering unifies adaptive and non-adaptive neural network optimization methods NIPS 2020
An Improved Analysis of Stochastic Gradient Descent with Momentum NIPS 2020
DisARM: An Antithetic Gradient Estimator for Binary Latent Variables NIPS 2020
Collegial Ensembles NIPS 2020
AdaBelief Optimizer: Adapting Stepsizes by the Belief in Observed Gradients NIPS 2020
Almost Surely Stable Deep Dynamics NIPS 2020
MMA Regularization: Decorrelating Weights of Neural Networks by Maximizing the Minimal Angles NIPS 2020
Generalization bound of globally optimal non-convex neural network training: Transportation map estimation by infinite dimensional Langevin dynamics NIPS 2020
Unifying Activation- and Timing-based Learning Rules for Spiking Neural Networks NIPS 2020
Estimating Training Data Influence by Tracing Gradient Descent NIPS 2020
Batch Normalization Biases Residual Blocks Towards the Identity Function in Deep Networks NIPS 2020
A Theoretical Framework for Target Propagation NIPS 2020
A Study on Encodings for Neural Architecture Search NIPS 2020
Learning Parities with Neural Networks NIPS 2020