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- Dictionarysparse/spɑːs/
adjective
- 1. thinly dispersed or scattered: "areas of sparse population"
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Aug 23, 2018 · 1. In mathematics, a dense graph is a graph in which the number of edges is close to the maximal number of edges. The opposite, a graph with only a few edges, is a sparse graph. The distinction between sparse and dense graphs is rather vague, and depends on the context. answered Feb 17, 2017 at 0:07.
Jul 6, 2011 · 27. In a regular database, rows are sparse but columns are not. When a row is created, storage is allocated for every column, irrespective of whether a value exists for that field (a field being storage allocated for the intersection of a row and and a column). This allows fixed length rows greatly improving read and write times.
Aug 7, 2008 · The compressed sparse row (CSR) or compressed row storage (CRS) format represents a matrix M by three (one-dimensional) arrays, that respectively contain nonzero values, the extents of rows, and column indices. It is similar to COO, but compresses the row indices, hence the name. This format allows fast row access and matrix-vector ...
May 17, 2021 · def sparse_(tensor, sparsity, std=0.01): with torch.no_grad(): tensor.normal_(0, std) tensor = F.dropout(tensor, sparsity) return tensor If you wish to enforce column, channel, etc-wise proportions of zeros (as opposed to just total proportion) you can implement logic similar to the original function.
Apr 8, 2014 · 2. Generally, it is said that a graph with n vertices is dense if it has Theta (n ^2) edges and is sparse otherwise. This means that a graph is dense if the average degree of each vertex is lineal, and sparse if sublineal. Sparsity does not deppend on size. For instance, trees are sparse (because a tree with n nodes has n-1 edges).
Sep 4, 2015 · I'm trying to build and update a sparse matrix as I read data from file. The matrix is of size 100000X40000. What is the most efficient way of updating multiple entries of the sparse matrix? specifically I need to increment each entry by 1. Let's say I have row indices [2, 236, 246, 389, 1691] and column indices [117, 3, 34, 2757, 74, 1635, 52]
Apr 23, 2016 · Dense Index. An index record is created for every row of the table. Records can be located directly as each record of the index holds the search key value and the pointer to the actual record. Sparse Index. Index records are created only for some of the records. To locate a record: While Dense Indexes are great for search and select operations ...
Jan 14, 2011 · Scipy doesn't have a way to do this without copying the data but you can do it yourself by changing the attributes that define the sparse matrix. There are 4 attributes that make up the csr_matrix: data: An array containing the actual values in the matrix. indices: An array containing the column index corresponding to each value in data
Sep 16, 2018 · In case of larger sparse matrices you may also want to look at the .reserve() function in order to allocate memory before filling the elements. The .reserve() function can be used to provide an estimate of the number of non-zero entries per column (or row, depending on the storage order.
So things like matrix product (the dot product for numpy arrays) and equation solvers are well developed. My rough experience is that a sparse csr matrix product has to have a 1% sparsity to be faster than the equivalent dense dot operation - in other words, one nonzero value for every 99 zeros. (but see tests below) But people also try to use ...
