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

Domain Generalization Guided by Gradient Signal to Noise Ratio of Parameters ICCV 2023
Towards Data-Algorithm Dependent Generalization: a Case Study on Overparameterized Linear Regression NIPS 2023
Provable Advantage of Curriculum Learning on Parity Targets with Mixed Inputs NIPS 2023
QuACK: Accelerating Gradient-Based Quantum Optimization with Koopman Operator Learning NIPS 2023
Learning threshold neurons via edge of stability NIPS 2023
A Unified Discretization Framework for Differential Equation Approach with Lyapunov Arguments for Convex Optimization NIPS 2023
Competitive Gradient Optimization ICML 2023
On Generalization of Decentralized Learning with Separable Data AISTATS 2023
Extending Kernel PCA through Dualization: Sparsity, Robustness and Fast Algorithms ICML 2023
Convergence of Alternating Gradient Descent for Matrix Factorization NIPS 2023
Training shallow ReLU networks on noisy data using hinge loss: when do we overfit and is it benign? NIPS 2023
SHOT: Suppressing the Hessian along the Optimization Trajectory for Gradient-Based Meta-Learning NIPS 2023
Approximate Regions of Attraction in Learning with Decision-Dependent Distributions AISTATS 2023
Aligning Gradient and Hessian for Neural Signed Distance Function NIPS 2023
Online Optimization over Riemannian Manifolds JMLR 2023
A Line-Search Descent Algorithm for Strict Saddle Functions with Complexity Guarantees JMLR 2023
Efficient Convex Optimization Requires Superlinear Memory (Extended Abstract) IJCAI 2023
Riemannian Accelerated Gradient Methods via Extrapolation AISTATS 2023
Linear Convergence of Gradient Descent For Finite Width Over-parametrized Linear Networks With General Initialization AISTATS 2023
Optimizing ROC Curves with a Sort-Based Surrogate Loss for Binary Classification and Changepoint Detection JMLR 2023
Elastic Gradient Descent, an Iterative Optimization Method Approximating the Solution Paths of the Elastic Net JMLR 2023
Memory-Constrained Algorithms for Convex Optimization NIPS 2023
Grad-PU: Arbitrary-Scale Point Cloud Upsampling via Gradient Descent With Learned Distance Functions CVPR 2023
Benign overfitting of non-smooth neural networks beyond lazy training AISTATS 2023
3D Shape Reconstruction of Semi-Transparent Worms CVPR 2023