← Optimization & Theory
Machine Learning › Optimization & Theory ›

Neural Network Optimization

3648 directly classified papers

Papers per year

Papers

Super-efficiency of automatic differentiation for functions defined as a minimum ICML 2020
Dynamical Systems as Temporal Feature Spaces JMLR 2020
AdaGrad stepsizes: Sharp convergence over nonconvex landscapes JMLR 2020
Asymptotic Analysis via Stochastic Differential Equations of Gradient Descent Algorithms in Statistical and Computational Paradigms JMLR 2020
Estimate Sequences for Stochastic Composite Optimization: Variance Reduction, Acceleration, and Robustness to Noise JMLR 2020
Chaining Meets Chain Rule: Multilevel Entropic Regularization and Training of Neural Networks JMLR 2020
Convergence Rates for the Stochastic Gradient Descent Method for Non-Convex Objective Functions JMLR 2020
A Unified Framework of Online Learning Algorithms for Training Recurrent Neural Networks JMLR 2020
Directional convergence and alignment in deep learning NIPS 2020
Noise Isn’t Always Negative: Countering Exposure Bias in Sequence-to-Sequence Inflection Models COLING 2020
NITK NLP at FinCausal-2020 Task 1 Using BERT and Linear models. COLING 2020
syrapropa at SemEval-2020 Task 11: BERT-based Models Design for Propagandistic Technique and Span Detection COLING 2020
Enhancing Urban Flow Maps via Neural ODEs IJCAI 2020
Optimization Learning: Perspective, Method, and Applications IJCAI 2020
Rethinking Skip Connection with Layer Normalization COLING 2020
Context-Aware Cross-Attention for Non-Autoregressive Translation COLING 2020
Accelerating Stratified Sampling SGD by Reconstructing Strata IJCAI 2020
Marthe: Scheduling the Learning Rate Via Online Hypergradients IJCAI 2020
Proximal Gradient Algorithm with Momentum and Flexible Parameter Restart for Nonconvex Optimization IJCAI 2020
Porous Lattice Transformer Encoder for Chinese NER COLING 2020
The Transference Architecture for Automatic Post-Editing COLING 2020
Closing the Generalization Gap of Adaptive Gradient Methods in Training Deep Neural Networks IJCAI 2020
Generalization bound of globally optimal non-convex neural network training: Transportation map estimation by infinite dimensional Langevin dynamics NIPS 2020
Towards Theoretically Understanding Why Sgd Generalizes Better Than Adam in Deep Learning NIPS 2020
Beyond Lazy Training for Over-parameterized Tensor Decomposition NIPS 2020