Visibility Optimization Using Variational Approaches
نویسندگان
چکیده
منابع مشابه
Visibility Optimization Using Variational Approaches
Constructing the visible and invisible regions of an observer due to the presence of obstacles in the environment has played a central role in many applications. It can also be a first step. In this paper, we adopt a visibility algorithm that can produce a variety of general information to handle the optimization of visibility information. Through the use of level set tools, gradient flow, fini...
متن کاملEfficient Convex Optimization Approaches to Variational Image Fusion
Image fusion is an imaging technique to visualize information from multiple imaging sources by one single image, which is widely used in remote sensing, medical imaging etc. In this work, we study two variational approaches to image fusion which are closely related to the standard TV-L2 and TV-L1 image approximation methods. We investigate their convex optimization formulations, under the persp...
متن کاملVariational density matrix optimization using semidefinite programming
programming Brecht Verstichel, ∗ Helen van Aggelen, Dimitri Van Neck, Paul W. Ayers, and Patrick Bultinck Center for Molecular Modeling, Ghent University, Technologiepark 903, 9052 Zwijnaarde, Belgium Department of Inorganic and Physical Chemistry, Ghent University, Krijgslaan 281 (S3), 9000 Gent, Belgium Department of Chemistry, McMaster University, Hamilton, Ontario, L8S 4M1, Canada Abstract ...
متن کاملVariational Optimization
We discuss a general technique that can be used to form a differentiable bound on the optima of non-differentiable or discrete objective functions. We form a unified description of these methods and consider under which circumstances the bound is concave. In particular we consider two concrete applications of the method, namely sparse learning and support vector classification. 1 Optimization b...
متن کاملOptimization by Variational Bounding
We discuss a general technique that forms a differentiable bound on non-differentiable objective functions by bounding the function optimum by its expectation with respect to a parametric variational distribution. We describe sufficient conditions for the bound to be convex with respect to the variational parameters. As example applications we consider variants of sparse linear regression and S...
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: Communications in Mathematical Sciences
سال: 2005
ISSN: 1539-6746,1945-0796
DOI: 10.4310/cms.2005.v3.n3.a8