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

Accelerated Algorithms for Smooth Convex-Concave Minimax Problems with O(1/k^2) Rate on Squared Gradient Norm ICML 2021
Asynchronous Decentralized Online Learning NIPS 2021
On Continuous Local BDD-Based Search for Hybrid SAT Solving AAAI 2021
Shuffling Recurrent Neural Networks AAAI 2021
Why Adversarial Interaction Creates Non-Homogeneous Patterns: A Pseudo-Reaction-Diffusion Model for Turing Instability AAAI 2021
Convergence of adaptive algorithms for constrained weakly convex optimization NIPS 2021
A Dynamical View on Optimization Algorithms of Overparameterized Neural Networks AISTATS 2021
Mirror Descent View for Neural Network Quantization AISTATS 2021
CANITA: Faster Rates for Distributed Convex Optimization with Communication Compression NIPS 2021
Non-asymptotic convergence bounds for Wasserstein approximation using point clouds NIPS 2021
Conflict-Averse Gradient Descent for Multi-task learning NIPS 2021
Understanding How Over-Parametrization Leads to Acceleration: A case of learning a single teacher neuron ACML 2021
On Optimal Interpolation in Linear Regression NIPS 2021
Learning with Gradient Descent and Weakly Convex Losses AISTATS 2021
Improved Analysis for Dynamic Regret of Strongly Convex and Smooth Functions L4DC 2021
Gradient-based Hyperparameter Optimization Over Long Horizons NIPS 2021
Task similarity aware meta learning: theory-inspired improvement on MAML UAI 2021
The complexity of nonconvex-strongly-concave minimax optimization UAI 2021
Beyond Reptile: Meta-Learned Dot-Product Maximization between Gradients for Improved Single-Task Regularization EMNLP 2021
Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach EMNLP 2021
Constrained labeling for weakly supervised learning UAI 2021
An Even More Optimal Stochastic Optimization Algorithm: Minibatching and Interpolation Learning NIPS 2021
Averaging on the Bures-Wasserstein manifold: dimension-free convergence of gradient descent NIPS 2021
A Local Convergence Theory for Mildly Over-Parameterized Two-Layer Neural Network COLT 2021
SUPER-ADAM: Faster and Universal Framework of Adaptive Gradients NIPS 2021