Convergence guarantees for a class of non-convex and non-smooth optimization problems
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Publication:5214248
zbMath1446.90130arXiv1804.09629MaRDI QIDQ5214248
Koulik Khamaru, Martin J. Wainwright
Publication date: 7 February 2020
Full work available at URL: https://arxiv.org/abs/1804.09629
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Cites Work
- Unnamed Item
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- Proximal alternating linearized minimization for nonconvex and nonsmooth problems
- On functions representable as a difference of convex functions
- On gradients of functions definable in o-minimal structures
- A globally convergent algorithm for nonconvex optimization based on block coordinate update
- A proximal difference-of-convex algorithm with extrapolation
- DC formulations and algorithms for sparse optimization problems
- Calculus of the exponent of Kurdyka-Łojasiewicz inequality and its applications to linear convergence of first-order methods
- NP-hardness of deciding convexity of quartic polynomials and related problems
- Lower bounds for finding stationary points I
- Variations and extension of the convex-concave procedure
- Cubic regularization of Newton method and its global performance
- A Complete Characterization of the Gap between Convexity and SOS-Convexity
- Convergence Analysis of Alternating Direction Method of Multipliers for a Family of Nonconvex Problems
- Convergence analysis of a proximal point algorithm for minimizing differences of functions
- On the Complexity of Steepest Descent, Newton's and Regularized Newton's Methods for Nonconvex Unconstrained Optimization Problems
- Proximal Alternating Minimization and Projection Methods for Nonconvex Problems: An Approach Based on the Kurdyka-Łojasiewicz Inequality
- The Concave-Convex Procedure
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- High-Dimensional Statistics
- Gradient Descent Only Converges to Minimizers: Non-Isolated Critical Points and Invariant Regions
- Finite-Dimensional Variational Inequalities and Complementarity Problems
- The Łojasiewicz Inequality for Nonsmooth Subanalytic Functions with Applications to Subgradient Dynamical Systems
- Introduction to global optimization.