AbstractIt is shown how a matrix can be used to implement a class of dictionaries. Instead of the strong requirement of ascendingness of a linear array, the weaker requirement of ascendingness of a matrix is used. This results in implementations that are efficient in both computation time and storage usage
An implicit data structure for the dictionary problem maintains n data values in the first n locatio...
Evaluating an expression in linear algebra using the known Basic Linear Algebra Subprograms libr...
We address the problem of implementing data structures resilient to memory faults, which may arbitra...
AbstractIt is shown how a matrix can be used to implement a class of dictionaries. Instead of the st...
It is shown how a matrix can be used to implement a class of dictionaries. Instead of the strong req...
International audienceDictionary learning is a branch of signal processing and machine learning that...
A proof of concept is offered for the uniform representation of matrices serially in Morton-order (o...
We develop a prototype library for in-place (dense) matrix storage for-mat conversion between the ca...
Dictionaries are probably the most well studied class of data structures. A dictionary supports inse...
Dictionaries are fundamental data structures that associate values to a set of keys. They form the f...
AbstractA new formulation for LU decomposition allows efficient representation of intermediate matri...
Strassen's algorithm for matrix multiplication gains its lower arithmetic complexityatthe expe...
Dictionary learning is a branch of signal processing and machine learning that aims at finding a fra...
Given a rectangular matrix with more columns than rows, find a base of linear combinations of the ro...
We address the problem of implementing data structures resilient to memory faults, which may arbitra...
An implicit data structure for the dictionary problem maintains n data values in the first n locatio...
Evaluating an expression in linear algebra using the known Basic Linear Algebra Subprograms libr...
We address the problem of implementing data structures resilient to memory faults, which may arbitra...
AbstractIt is shown how a matrix can be used to implement a class of dictionaries. Instead of the st...
It is shown how a matrix can be used to implement a class of dictionaries. Instead of the strong req...
International audienceDictionary learning is a branch of signal processing and machine learning that...
A proof of concept is offered for the uniform representation of matrices serially in Morton-order (o...
We develop a prototype library for in-place (dense) matrix storage for-mat conversion between the ca...
Dictionaries are probably the most well studied class of data structures. A dictionary supports inse...
Dictionaries are fundamental data structures that associate values to a set of keys. They form the f...
AbstractA new formulation for LU decomposition allows efficient representation of intermediate matri...
Strassen's algorithm for matrix multiplication gains its lower arithmetic complexityatthe expe...
Dictionary learning is a branch of signal processing and machine learning that aims at finding a fra...
Given a rectangular matrix with more columns than rows, find a base of linear combinations of the ro...
We address the problem of implementing data structures resilient to memory faults, which may arbitra...
An implicit data structure for the dictionary problem maintains n data values in the first n locatio...
Evaluating an expression in linear algebra using the known Basic Linear Algebra Subprograms libr...
We address the problem of implementing data structures resilient to memory faults, which may arbitra...
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