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

Learning in Stochastic Monotone Games with Decision-Dependent Data AISTATS 2022
A proof of convergence for the gradient descent optimization method with random initializations in the training of neural networks with ReLU activation for piecewise linear target functions JMLR 2022
Training Two-Layer ReLU Networks with Gradient Descent is Inconsistent JMLR 2022
Early Stopping for Iterative Regularization with General Loss Functions JMLR 2022
Practical Adversarial Attacks on Spatiotemporal Traffic Forecasting Models NIPS 2022
The First Optimal Algorithm for Smooth and Strongly-Convex-Strongly-Concave Minimax Optimization NIPS 2022
Faster Stochastic Algorithms for Minimax Optimization under Polyak-{\L}ojasiewicz Condition NIPS 2022
Non-asymptotic and Accurate Learning of Nonlinear Dynamical Systems JMLR 2022
Gradient Descent: The Ultimate Optimizer NIPS 2022
Overparameterization of Deep ResNet: Zero Loss and Mean-field Analysis JMLR 2022
How to Learn when Data Gradually Reacts to Your Model AISTATS 2022
AdaLoss: A Computationally-Efficient and Provably Convergent Adaptive Gradient Method AAAI 2022
Optimality and Stability in Non-Convex Smooth Games JMLR 2022
Scaling and Scalability: Provable Nonconvex Low-Rank Tensor Completion AISTATS 2022
Annihilation of Spurious Minima in Two-Layer ReLU Networks NIPS 2022
Deep Architecture Connectivity Matters for Its Convergence: A Fine-Grained Analysis NIPS 2022
Learning from Mistakes – a Framework for Neural Architecture Search AAAI 2022
Globally Gated Deep Linear Networks NIPS 2022
Provable Acceleration of Heavy Ball beyond Quadratics for a Class of Polyak-Lojasiewicz Functions when the Non-Convexity is Averaged-Out ICML 2022
Injecting Logical Constraints into Neural Networks via Straight-Through Estimators ICML 2022
Neural Network Weights Do Not Converge to Stationary Points: An Invariant Measure Perspective ICML 2022
Feedback Gradient Descent: Efficient and Stable Optimization with Orthogonality for DNNs AAAI 2022
A Convergent and Dimension-Independent Min-Max Optimization Algorithm ICML 2022
A Simple Guard for Learned Optimizers ICML 2022
Projective Manifold Gradient Layer for Deep Rotation Regression CVPR 2022