There is considerable recent work on redesigning database and data mining algorithms to make full use of hardware resources and minimize the memory stalls and branch mispredictions. These techniques...S. Manegol
The new orthogonal feature space often produces a better fit for conventional machine learning algorithms to learn accurate classifiers, compared to the ones learned from the original feature space. However, such feature extraction process does not consider temporal or spatial correlation of the data, ...
In a statically-typed language, overloads dispatch based on data types, and in an ideal world, on what concepts they model. In a well-designed generic program in a statically-typed language you have high level generic algorithms built around smaller and smaller algorithms, each operating on mo...
Computer Science - Data Structures and AlgorithmsA string matching -- and more generally, sequence matching -- algorithm is presented that has a linear worst-case computing time bound, a low worst-case bound on the number of comparisons (2n), and sublinear average-case behavior that is better...
ACOLITE combines the atmospheric correction algorithms for aquatic applications of various satellite missions developed at RBINS. This repository hosts the (more) generic version of ACOLITE with the aim of bringing together the processing of all different sensors. This new generic version was started ...
A distinctive feature of the library is that all supported meshes inherit from a unique base class that implements their common traits, permitting to deploy algorithms that operate onabstractmeshes that may be any of the above. This allows to implement algorithms just once and run the same code...
Scoring methods based on machine learning have made substantial progress with the explosive growth of experimental protein–ligand interaction data. Various machine learning algorithms and neural network architectures, such as three-dimensional convolutional neural networks10,11and graph convolutional neural net...
A GA is a metaheuristic inspired by the natural selection process. It belongs to the larger class of evolutionary algorithms (EAs), and is commonly used in computer science to generate optimized solutions to complex search problems. To this end, a GA relies on bio-inspired operators such as ...
An analysis class groups all components within a global dynamical system and applies Newton iterations and/or line search algorithms to anihilate the residual vector at each timestep. The interface design to element objects must be based on the data structure needed to answer questions asked by ...
Extensive work on improving the algorithms’ performance has led to significant improvements of computational time (discussed in Section 5). 4.1.2 Network flow problem In contrast to the duty-based (also referred to as path-flow) model formulation in the form of SCP or SPP, a group of ...