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of 302
pro vyhledávání: '"Nobel Andrew"'
We study optimal transport for stationary stochastic processes taking values in finite spaces. In order to reflect the stationarity of the underlying processes, we restrict attention to stationary couplings, also known as joinings. The resulting opti
Externí odkaz:
http://arxiv.org/abs/2107.11858
We describe and study a transport based procedure called NetOTC (network optimal transition coupling) for the comparison and alignment of two networks. The networks of interest may be directed or undirected, weighted or unweighted, and may have disti
Externí odkaz:
http://arxiv.org/abs/2106.07106
Publikováno v:
Journal of Machine Learning Research Vol. 24, 2023
Datasets in which measurements of two (or more) types are obtained from a common set of samples arise in many scientific applications. A common problem in the exploratory analysis of such data is to identify groups of features of different data types
Externí odkaz:
http://arxiv.org/abs/2009.05079
We study the optimal transport problem for pairs of stationary finite-state Markov chains, with an emphasis on the computation of optimal transition couplings. Transition couplings are a constrained family of transport plans that capture the dynamics
Externí odkaz:
http://arxiv.org/abs/2006.07998
We consider random recursive trees that are grown via community modulated schemes that involve random attachment or degree based attachment. The aim of this paper is to derive general techniques based on continuous time embedding to study such models
Externí odkaz:
http://arxiv.org/abs/2004.02697
Publikováno v:
BMC Genomics, Vol 11, Iss 1, p 574 (2010)
Abstract Background Analysis of microarray experiments often involves testing for the overrepresentation of pre-defined sets of genes among lists of genes deemed individually significant. Most popular gene set testing methods assume the independence
Externí odkaz:
https://doaj.org/article/eb95fe612f9e4291815012fd45f6a4f5
Autor:
Perreard Laurent, Palazzo Juan P, Dreher Donna, Orrico Alejandra, Tretiakova Maria, Nanda Rita, Liu Yudong, Wu Junyuan, Sawyer Lynda R, Ewend Matthew G, Parker Joel, Nobel Andrew, Dressler Lynn, Reynolds Evangeline, Carey Lisa A, Livasy Chad, Qaqish Bahjat F, He Xiaping, Marron JS, Oh Daniel S, Fan Cheng, Hu Zhiyuan, Nelson Edward, Mone Mary, Hansen Heidi, Mullins Michael, Quackenbush John F, Ellis Matthew J, Olopade Olufunmilayo I, Bernard Philip S, Perou Charles M
Publikováno v:
BMC Genomics, Vol 7, Iss 1, p 96 (2006)
Abstract Background Validation of a novel gene expression signature in independent data sets is a critical step in the development of a clinically useful test for cancer patient risk-stratification. However, validation is often unconvincing because t
Externí odkaz:
https://doaj.org/article/c8fa0c56fa604033aa5ee4d225f1d530
In this paper we consider a Bayesian framework for making inferences about dynamical systems from ergodic observations. The proposed Bayesian procedure is based on the Gibbs posterior, a decision theoretic generalization of standard Bayesian inferenc
Externí odkaz:
http://arxiv.org/abs/1901.08641
Akademický článek
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We consider the problem of identifying stable sets of mutually associated features in moderate or high-dimensional binary data. In this context we develop and investigate a method called Latent Association Mining for Binary Data (LAMB). The LAMB meth
Externí odkaz:
http://arxiv.org/abs/1711.10427