Finding Submodularity Hidden in Symmetric Difference
نویسندگان
چکیده
منابع مشابه
Finding the Submodularity Hidden in Symmetric Difference
A fundamental property of convex functions in continuous space is that the convexity is preserved under affine transformations. A set function f on a finite set V is submodular if f(X) + f(Y ) ≥ f(X ∪ Y )− f(X ∩ Y ) for any pair X,Y ⊆ V . The symmetric difference transformation (SD-transformation) of f by a canonical set S ⊆ V is a set function g given by g(X) = f(X M S) for X ⊆ V , where X M S...
متن کاملFinding Hidden Motives
One of this year’s Oscar-winning movies, The Big Short, tells the entertaining story of a ragtag bunch who foresaw and capitalized on the housing bubble of the mid-2000s. The factors contributing to economic bubbles and their collapses are complex and heavily debated, but getting a clearer picture of how they arise and how we might avoid them in the future would seem particularly important as o...
متن کاملFinding Hidden Hamiltonian Cycles
Consider a random graph G composed of a Hamiltonian cycle on n labeled vertices and dn random edges that “hide” the cycle. Is it possible to unravel the structure, that is, to efficiently find a Hamiltonian cycle in G? We describe an O(n3 logn) steps algorithm A for this purpose, and prove that it succeeds almost surely. Part one of A properly covers the “trouble spots” of G by a collection of ...
متن کاملAN ALGORITHM FOR FINDING THE EIGENPAIRS OF A SYMMETRIC MATRIX
The purpose of this paper is to show that ideas and techniques of the homotopy continuation method can be used to find the complete set of eigenpairs of a symmetric matrix. The homotopy defined by Chow, Mallet- Paret and York [I] may be used to solve this problem with 2""-n curves diverging to infinity which for large n causes a great inefficiency. M. Chu 121 introduced a homotopy equation...
متن کاملFinding Bayesian Difference Networks
Often in biological analysis, identifying the differences in the interactions among attributes between two subpopulations—a difference network—is important. For example, identifying the gene interactions that differ between tumor and non-tumor patients would be extremely useful. We have developed a method based upon Bayesian network learning for finding interactions among attributes that appear...
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: SIAM Journal on Discrete Mathematics
سال: 2020
ISSN: 0895-4801,1095-7146
DOI: 10.1137/19m1243361