Leveraging for big data regression
Rapid advance in science and technology in the past decade brings an extraordinary
amount of data, offering researchers an unprecedented opportunity to tackle complex …
amount of data, offering researchers an unprecedented opportunity to tackle complex …
[HTML][HTML] Parallel ant colony optimization on multi-core SIMD CPUs
Y Zhou, F He, N Hou, Y Qiu - Future Generation Computer Systems, 2018 - Elsevier
Ant colony optimization (ACO) is a population-based metaheuristic for solving hard
combinatorial optimization problems. Many studies are dedicated to accelerating ACO by …
combinatorial optimization problems. Many studies are dedicated to accelerating ACO by …
Architecturally truly diverse systems: A review
RD Chamberlain - Future Generation Computer Systems, 2020 - Elsevier
The pairing of traditional multicore processors with accelerators of various forms (eg,
graphics engines, reconfigurable logic) can be referred to generally as architecturally …
graphics engines, reconfigurable logic) can be referred to generally as architecturally …
Efficient big data model selection with applications to fraud detection
G Vaughan - International Journal of Forecasting, 2020 - Elsevier
As the volume and complexity of data continues to grow, more attention is being focused on
solving so-called big data problems. One field where this focus is pertinent is credit card …
solving so-called big data problems. One field where this focus is pertinent is credit card …
A generic vectorization scheme and a GPU kernel for the phylogenetic likelihood library
F Izquierdo-Carrasco, N Alachiotis… - … on Parallel & …, 2013 - ieeexplore.ieee.org
Highly optimized library implementations for important scientific kernels can improve
scientific productivity. To this end, we are currently develo** the Phylogenetic Likelihood …
scientific productivity. To this end, we are currently develo** the Phylogenetic Likelihood …
Effective statistical methods for big data analytics
With advances in technologies in the past decade, the amount of data generated and
recorded has grown enormously in virtually all fields of industry and science. This …
recorded has grown enormously in virtually all fields of industry and science. This …
Predicting the performance measures of a message-passing multiprocessor architecture using artificial neural networks
EIM Zayid, MF Akay - Neural Computing and Applications, 2013 - Springer
In this paper, we develop multi-layer feed-forward artificial neural network (MFANN) models
for predicting the performance measures of a message-passing multiprocessor architecture …
for predicting the performance measures of a message-passing multiprocessor architecture …
A hybrid approach to parallelize a fast non‐dominated sorting genetic algorithm for phylogenetic inference
S Santander‐Jiménez… - Concurrency and …, 2015 - Wiley Online Library
The field of computational biology encloses a wide range of optimization problems that show
non‐deterministic polynomial‐time hard complexities. Nowadays, phylogeneticians are …
non‐deterministic polynomial‐time hard complexities. Nowadays, phylogeneticians are …
On the design of shared memory approaches to parallelize a multiobjective bee-inspired proposal for phylogenetic reconstruction
S Santander-Jimenez, MA Vega-Rodriguez - Information Sciences, 2015 - Elsevier
Current efforts in solving computationally demanding optimization problems in
bioinformatics rely on the combination of bioinspired computing and parallelism. The …
bioinformatics rely on the combination of bioinspired computing and parallelism. The …
[HTML][HTML] An efficient GPU acceleration technique for CBCT based on memory aware optimization scheme
Among many of the image reconstruction techniques; the Feldkamp-Davis-Kress (FDK) is
considered the most practical algorithm that used in clinical cone-beam Computed …
considered the most practical algorithm that used in clinical cone-beam Computed …