[HAL] BigDataFr recommends: Random Forests for Big Data

BigDataFr recommends: Random Forests for Big Data Abstract […] Big Data is one of the major challenges of statistical science and has numerous consequences from algorithmic and theoretical viewpoints. Big Data always involve massive data but they also often include online data and data heterogeneity. Recently some statistical methods have been adapted to process Big […]

[Dataconomy] BigDataFr recommends: Securing Competitive Advantage with Machine Learning

BigDataFr recommends: Securing Competitive Advantage with Machine Learning […] Business dynamics are evolving with every passing second. There is no doubt that the competition in today’s business world is much more intense than it was a decade ago. Companies are fighting to hold on to any advantages. Digitalization and the introduction of machine learning into […]

[Forbes France] BigDataFr recommande : Pourquoi Le Commerce “Physique” Pourrait Reprendre La Main

BigDataFr recommande : Pourquoi Le Commerce “Physique” Pourrait Reprendre La Main […] La révolution du web a clairement entraîné de profonds changements chez les acheteurs et de facto chez ceux qui sont donc devenus des e-commerçants. Toutefois, suite à la frénésie du tout digital des premières années, la donne est en train de changer vers […]

[HAL] BigDataFr recommends: Eley: On the Effectiveness of Burst Buffers for Big Data Processing in HPC systems

BigDataFr recommends: Eley: On the Effectiveness of Burst Buffers for Big Data Processing in HPC systems Abstract […] Burst Buffer is an effective solution for reducing the data transfer time and the I/O interference in HPC systems. Extending Burst Buffers (BBs) to handle Big Data applications is challenging because BBs must account for the large […]

[arXiv] BigDataFr recommends: Visualization of Big Spatial Data using Coresets for Kernel Density Estimates

BigDataFr recommends: Visualization of Big Spatial Data using Coresets for Kernel Density Estimates […] Subjects: Human-Computer Interaction (cs.HC); Computational Geometry (cs.CG) The size of large, geo-located datasets has reached scales where visualization of all data points is inefficient. Random sampling is a method to reduce the size of a dataset, yet it can introduce unwanted […]

[La Tribune] BigDataFr recommande : La France se prépare au futur de son industrie

BigDataFr recommande : La France se prépare au futur de son industrie […] Robots et capteurs, simulation et connectivité, intégration de la culture digitale et bouleversement des modèles économiques, l’industrie se transforme en profondeur. Cette mutation est organisationnelle autant que technologique. Toutes les entreprises françaises n’ont pas encore pris conscience des changements profonds qui nécessitent […]

[arXiv] BigDataFr recommends: A European research roadmap for optimizing societal impact of big data on environment and energy efficiency

BigDataFr recommends: A European research roadmap for optimizing societal impact of big data on environment and energy efficiency […] We present a roadmap to guide European research efforts towards a socially responsible big data economy that maximizes the positive impact of big data in environment and energy efficiency. The goal of the roadmap is to […]