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SPARSE contains TALLY, the class of unary languages, since these have at most one string of any one length. Although not all languages in P/poly are sparse, there is a polynomial-time Turing reduction from any language in P/poly to a sparse language. [1] Fortune showed in 1979 that if any sparse language is co-NP-complete, then P = NP. [2]
Sparse may refer to: Sparse, a software static analysis tool; Sparse language, a type of formal language in computational complexity theory; Sparse matrix, in numerical analysis, a matrix populated primarily with zeros; Sparse file, a computer file mostly empty; Sparse network, a network with many fewer connections than possible
A simple unweighted network of size is called sparse if the number of links in it is much smaller than the maximum possible number of links : [1] = (). In any given (real) network, the number of nodes N and links M are just two numbers, therefore the meaning of the much smaller sign (above) is purely colloquial and informal, and so are statements like "many real networks are sparse."
After printing, early versions of the Canzoniere were illuminated with pictures. Il Canzoniere (Italian pronunciation: [il kantsoˈnjɛːre]; English: Song Book), also known as the Rime Sparse (English: Scattered Rhymes), but originally titled Rerum vulgarium fragmenta (English: Fragments of common things, that is Fragments composed in vernacular), is a collection of poems written in the ...
Alogia can be brought on by frontostriatal dysfunction which causes degradation of the semantic store, the center located in the temporal lobe that processes meaning in language. A subgroup of chronic schizophrenia patients in a word generation experiment generated fewer words than the unaffected subjects and had limited lexicons , evidence of ...
The correlation between aridity and sparse population is complex and dynamic, varying by culture, era, and technologies; thus the use of the word desert can cause confusion. In English before the 20th century, desert was often used in the sense of "unpopulated area", without specific reference to aridity ; [ 2 ] but today the word is most often ...
Sparse approximation ideas and algorithms have been extensively used in signal processing, image processing, machine learning, medical imaging, array processing, data mining, and more. In most of these applications, the unknown signal of interest is modeled as a sparse combination of a few atoms from a given dictionary, and this is used as the ...
Disadvantages are that sparse files may become fragmented; file system free space reports may be misleading; filling up file systems containing sparse files can have unexpected effects (such as disk-full or quota-exceeded errors when merely overwriting an existing portion of a file that happened to have been sparse); and copying a sparse file with a program that does not explicitly support ...