scientific article; zbMATH DE number 7370585
From MaRDI portal
Publication:4998970
Chirag Gupta, Sivaraman Balakrishnan, Aaditya Ramdas
Publication date: 9 July 2021
Full work available at URL: https://arxiv.org/abs/1908.01089
Title: zbMATH Open Web Interface contents unavailable due to conflicting licenses.
optimizationcondition numbertrajectory analysisself-contracted curvesPolyak-Kurdyka-Łojasiewicz functions
Related Items (4)
Loss landscapes and optimization in over-parameterized non-linear systems and neural networks ⋮ Global convergence of the gradient method for functions definable in o-minimal structures ⋮ The slope robustly determines convex functions ⋮ Ubiquitous algorithms in convex optimization generate self-contracted sequences
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- On lower complexity bounds for large-scale smooth convex optimization
- Statistical guarantees for the EM algorithm: from population to sample-based analysis
- Maximum length of steepest descent curves for quasi-convex functions
- Asymptotic behaviour of self-contracted planar curves and gradient orbits of convex functions
- On gradients of functions definable in o-minimal structures
- The landscape of empirical risk for nonconvex losses
- Rectifiability of self-contracted curves in the Euclidean space and applications
- Self-contracted curves in Riemannian manifolds
- First-order methods almost always avoid strict saddle points
- Forward stagewise regression and the monotone lasso
- Convex regions on the \(n\)-dimensional spherical surface
- The Rate of Convergence of Nesterov's Accelerated Forward-Backward Method is Actually Faster Than $1/k^2$
- Theoretical Insights Into the Optimization Landscape of Over-Parameterized Shallow Neural Networks
- 10.1162/153244302760200704
- A Nearly-Linear Bound for Chasing Nested Convex Bodies
- Self-contracted curves have finite length
- Self-contracted curves are gradient flows of convex functions
- The Łojasiewicz Inequality for Nonsmooth Subanalytic Functions with Applications to Subgradient Dynamical Systems
- Some methods of speeding up the convergence of iteration methods
This page was built for publication:
