Distributed Coordination for Nonsmooth Convex Optimization via Saddle-Point Dynamics
نویسندگان
چکیده
منابع مشابه
Saddle Point Seeking for Convex Optimization Problems
In this paper, we consider convex optimization problems with constraints. By combining the idea of a Lie bracket approximation for extremum seeking systems and saddle point algorithms, we propose a feedback which steers a single-integrator system to the set of saddle points of the Lagrangian associated to the convex optimization problem. We prove practical uniform asymptotic stability of the se...
متن کاملNonsmooth Coordination and Geometric Optimization via Distributed Dynamical Systems
Emerging applications for networked and cooperative robots motivate the study of motion coordination for groups of agents. For example, it is envisioned that groups of agents will perform a variety of useful tasks including surveillance, exploration, and environmental monitoring. This paper deals with basic interactions among mobile agents such as “move away from the closest other agent” or “mo...
متن کاملSVM via Saddle Point Optimization: New Bounds and Distributed Algorithms
Support Vector Machine is one of the most classical approaches for classification and regression. Despite being studied for decades, obtaining practical algorithms for SVM is still an active research problem in machine learning. In this paper, we propose a new perspective for SVM via saddle point optimization. We provide an algorithm which achieves (1 − )-approximations with running time Õ(nd +...
متن کاملNonsmooth interval-valued optimization and saddle-point optimality criteria
In this article, we focus our attention on a nonsmooth interval-valued optimization problem and establish sufficient optimality conditions for a feasible solution to be a LU optimal solution under the invexity assumption. Appropriate duality theorems for Wolfe and Mond-Weir type duals are presented in order to relate the LU optimal solution of primal and dual programs. Moreover, saddle-point ty...
متن کاملA primal-dual algorithm framework for convex saddle-point optimization
In this study, we introduce a primal-dual prediction-correction algorithm framework for convex optimization problems with known saddle-point structure. Our unified frame adds the proximal term with a positive definite weighting matrix. Moreover, different proximal parameters in the frame can derive some existing well-known algorithms and yield a class of new primal-dual schemes. We prove the co...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Nonlinear Science
سال: 2018
ISSN: 0938-8974,1432-1467
DOI: 10.1007/s00332-018-9516-4