conftrace_

gradient descent

1144 papers

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Also known as

GD

Co-occurring keywords

neural network (6616) neural network optimization (1293) convex optimization (1321) non-convex optimization (547) convergence rate (607) stochastic optimization (1060) convergence analysis (395) stochastic gradient descent (1091) nonconvex optimization (316) implicit bia (107)

Papers

A Dynamical Central Limit Theorem for Shallow Neural Networks NIPS 2020
Automatic Differentiation of Some First-Order Methods in Parametric Optimization AISTATS 2020
Sparse and Low-rank Tensor Estimation via Cubic Sketchings AISTATS 2020
Convergence Rates of Gradient Descent and MM Algorithms for Bradley-Terry Models AISTATS 2020
On the Convergence Theory of Gradient-Based Model-Agnostic Meta-Learning Algorithms AISTATS 2020
Elimination of All Bad Local Minima in Deep Learning AISTATS 2020
99% of Worker-Master Communication in Distributed Optimization Is Not Needed UAI 2020
Winnowing with Gradient Descent COLT 2020
Complexity Guarantees for Polyak Steps with Momentum COLT 2020
Kernel and Rich Regimes in Overparametrized Models COLT 2020
A Tight and Unified Analysis of Gradient-Based Methods for a Whole Spectrum of Differentiable Games AISTATS 2020
Accelerated Factored Gradient Descent for Low-Rank Matrix Factorization AISTATS 2020
Low-rank regularization and solution uniqueness in over-parameterized matrix sensing AISTATS 2020
Orthogonal Gradient Descent for Continual Learning AISTATS 2020
Asymptotic Analysis via Stochastic Differential Equations of Gradient Descent Algorithms in Statistical and Computational Paradigms JMLR 2020
GradMix: Multi-source Transfer across Domains and Tasks WACV 2020
On the Convergence of Nesterov’s Accelerated Gradient Method in Stochastic Settings ICML 2020
High-dimensional Robust Mean Estimation via Gradient Descent ICML 2020
Multi-Task Learning with User Preferences: Gradient Descent with Controlled Ascent in Pareto Optimization ICML 2020
Effective Diversity in Population Based Reinforcement Learning NIPS 2020
On the linearity of large non-linear models: when and why the tangent kernel is constant NIPS 2020
From Trees to Continuous Embeddings and Back: Hyperbolic Hierarchical Clustering NIPS 2020
Regularized linear autoencoders recover the principal components, eventually NIPS 2020
Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions NIPS 2020
A Generalized Neural Tangent Kernel Analysis for Two-layer Neural Networks NIPS 2020