To support the above claims, we present eight recent implementations of various algorithms using the DataFlow paradigm, which show considerable speed-ups, power reductions and space savings over their implementation using the ControlFlow paradigm.
The future of the cloudless paradigm is one of increased efficiency, cost savings, and empowerment for enterprises, developers, and individuals alike. As a market for computing and algorithms develops, data storage and serverless execution will transition from the centralized cathedral of big cloud pro...
Huawei's logistics park in Dongguan underwent transformation that lasted for half a year. With the help of automated equipment and intelligent algorithms, delivery efficiency (volume of goods delivered per capita) has increased by 67%, and the delivery cycle has been shortened by over 50%. ...
It was noted that ensemble learning exceeded all the other seven algorithms. Ensemble learning achieved the highest AUC of 0.99, the highest G-Mean of 0.96, and an average F1-score of 0.97. Under a time-sensitive scenario, the Boosting method was a good choice as it spent less runtime ...
has grown exponentially, supported by the development of various algorithms, big data, and hardware such as graphic processing units170,171,172. DL involves a kind of neural network with multiple and deep layers; however, it can learn from raw data, features on hidden layers, and results173....
This provides a stronger compositional mode, as illustrated here, where a data structure can provide some basic parallel traversal methods (such as Graph::forall_nodes) that can then be reused to build more sophisticated parallel algorithms. Furthermore, it is convenient to describe all of the ...
This provides a stronger compositional mode, as illustrated here, where a data structure can provide some basic parallel traversal methods (such as Graph::forall_nodes) that can then be reused to build more sophisticated parallel algorithms. Furthermore, it is convenient to describe all...
Approaches to digitalization have included automated reference to library data as in the case of circular dichroism (CD) and/or the application of complex algorithms as in the case of mass spectrometry (MS)-based sequencing. “None of these approaches has yet been perfected, however, particularly...
In this regard, so-called naturally-inspired computations have been introduced, such as evolutionary computing; the genetic algorithm; genetic programming; particle swarm algorithms; ant algorithms; bacterial foraging algorithms; social algorithms; neuroevolution algorithms; artificial immune system algorithms;...
Dynamic data assimilation offers a suite of algorithms that merge measurement data with numerical simulations to predict accurate state trajectories. Meteorological centers rely heavily on data assimilation to achieve trustworthy… Deep Learning Machine Learning Reinforcement Learning Deep Reinforcement Learning...