Zobrazeno 1 - 10
of 343
pro vyhledávání: '"Black, Alexander"'
Autor:
Black, Alexander E., Criado, Francisco
Estimating the number of vertices of a two dimensional projection, called a shadow, of a polytope is a fundamental tool for understanding the performance of the shadow simplex method for linear programming among other applications. We prove multiple
Externí odkaz:
http://arxiv.org/abs/2406.06936
Although simplices are trivial from a linear optimization standpoint, the simplex algorithm can exhibit quite complex behavior. In this paper we study the behavior of max-slope pivot rules on (products of) simplices and describe the associated pivot
Externí odkaz:
http://arxiv.org/abs/2405.08506
Autor:
Black, Alexander E.
The existence of a pivot rule for the simplex method that guarantees a strongly polynomial run-time is a longstanding, fundamental open problem in the theory of linear programming. The leading pivot rule in theory is the shadow pivot rule, which solv
Externí odkaz:
http://arxiv.org/abs/2403.04886
We present VIXEN - a technique that succinctly summarizes in text the visual differences between a pair of images in order to highlight any content manipulation present. Our proposed network linearly maps image features in a pairwise manner, construc
Externí odkaz:
http://arxiv.org/abs/2402.19119
Representation learning aims to discover individual salient features of a domain in a compact and descriptive form that strongly identifies the unique characteristics of a given sample respective to its domain. Existing works in visual style represen
Externí odkaz:
http://arxiv.org/abs/2304.05755
Autor:
Black, Alexander E., Liu, Kevin, Mcdonough, Alex, Nelson, Garrett, Wigal, Michael C., Yin, Mei, Yoo, Youngho
A tanglegram consists of two rooted binary trees and a perfect matching between their leaves, and a planar tanglegram is one that admits a layout with no crossings. We show that the problem of generating planar tanglegrams uniformly at random reduces
Externí odkaz:
http://arxiv.org/abs/2304.05318
Autor:
Black, Alexander, Jenni, Simon, Bui, Tu, Tanjim, Md. Mehrab, Petrangeli, Stefano, Sinha, Ritwik, Swaminathan, Viswanathan, Collomosse, John
We propose VADER, a spatio-temporal matching, alignment, and change summarization method to help fight misinformation spread via manipulated videos. VADER matches and coarsely aligns partial video fragments to candidate videos using a robust visual d
Externí odkaz:
http://arxiv.org/abs/2303.13193
Autor:
Araujo, Igor, Black, Alexander E., Burcroff, Amanda, Gao, Yibo, Krueger, Robert A., McDonough, Alex
Given two vectors $u$ and $v$, their outer sum is given by the matrix $A$ with entries $A_{ij} = u_{i} + v_{j}$. If the entries of $u$ and $v$ are increasing and sufficiently generic, the total ordering of the entries of the matrix is a standard Youn
Externí odkaz:
http://arxiv.org/abs/2302.09194
We propose a self-supervised learning approach for videos that learns representations of both the RGB frames and the accompanying audio without human supervision. In contrast to images that capture the static scene appearance, videos also contain sou
Externí odkaz:
http://arxiv.org/abs/2302.07702