Zobrazeno 1 - 10
of 56
pro vyhledávání: '"LANGVILLE, AMY N."'
Autor:
Anderson, Paul E., Tat, Brandon, Ward, Charlie, Langville, Amy N., Pedings-Behling, Kathryn E.
We present an improved library for the ranking problem called RPLIB. RPLIB includes the following data and features. (1) Real and artificial datasets of both pairwise data (i.e., information about the ranking of pairs of items) and feature data (i.e.
Externí odkaz:
http://arxiv.org/abs/2206.11258
Recently, Anderson et al. (2019) proposed the concept of rankability, which refers to a dataset's inherent ability to produce a meaningful ranking of its items. In the same paper, they proposed a rankability measure that is based on a integer program
Externí odkaz:
http://arxiv.org/abs/1912.00275
Publikováno v:
In Linear Algebra and Its Applications 1 March 2020 588:81-100
It is well known that good initializations can improve the speed and accuracy of the solutions of many nonnegative matrix factorization (NMF) algorithms. Many NMF algorithms are sensitive with respect to the initialization of W or H or both. This is
Externí odkaz:
http://arxiv.org/abs/1407.7299
Autor:
Langville, Amy N.
Many very large Markov chains can be modeled efficiently as Stochastic Automata Networks (SANs). A SAN iscomposed of individual automata that, for the most part, act independently, requiring only infrequentinteraction. SANs represent the generator ma
Externí odkaz:
http://www.lib.ncsu.edu/theses/available/etd-20020326-002140
Autor:
Langville, Amy N., Stewart, William J.
Title from eBook title screen (viewed on August 3, 2006).
Publikováno v:
Foundations of Data Science; Sep2023, Vol. 5 Issue 3, p321-339, 19p
Autor:
Anderson, Paul E., Langville, Amy N., Pedings-Behling, Kathryn E., Tat, Brandon, Ward, Charlie
Publikováno v:
Optimization & Engineering; Sep2023, Vol. 24 Issue 3, p2213-2228, 16p