[HAL] BigDataFr recommends: Computing Dense Tensor Decompositions with Optimal Dimension Trees

BigDataFr recommends: Computing Dense Tensor Decompositions with Optimal Dimension Trees Abstract […] Dense tensor decompositions have been widely used in many signal processing problems including analyzing speech signals, identifying the localization of signal sources, and many other communication applications. Computing these decompositions poses major computational challenges for big datasets emerging in these domains. CANDECOMP/PARAFAC (CP) […]

[arXiv] BigDataFr recommends: Strategies for Big Data Analytics through Lambda Architectures in Volatile Environments

BigDataFr recommends: Strategies for Big Data Analytics through Lambda Architectures in Volatile Environments […] Expectations regarding the future growth of Internet of Things (IoT)-related technologies are high. These expectations require the realization of a sustainable general purpose application framework that is capable to handle these kinds of environments with their complexity in terms of heterogeneity […]

[La Tribune] BigDataFr recommande : Cycle de la hype 2017 : quelles sont les technologies les plus en vogue du moment ?

BigDataFr recommande : Cycle de la hype 2017 : quelles sont les technologies les plus en vogue du moment ? […] Le monde ne se réveille pas un beau matin avec une nouvelle technologie révolutionnaire à sa disposition, prête à être utilisée par tous. Non, l’adoption d’une innovation prend du temps. De la création d’une […]

[Datasciencecentral] BigDataFr recommends: More on Fully Automated Machine Learning

BigDataFr recommends: More on Fully Automated Machine Learning […] Recently we’ve written a series of articles on Automated Machine Learning (AML) which are platforms or packages designed to take over the most repetitive elements of preparing predictive models.  Typically these cover cleaning, preprocessing, some feature engineering, feature selection, and then model creation using one or […]

[Dataconomy] BigDataFr recommends: Steering Big Data Projects in the Modern Enterprise

BigDataFr recommends: Steering Big Data Projects in the Modern Enterprise […] Just a few years ago, enterprise organizations had to be convinced that Big Data was a real-world opportunity worth investing in. By 2016, 63% of those enterprise leaders were saying they considered Big Data and advanced analytics initiatives a necessity in order to remain […]

[La Tribune] BigDataFr recommande : Quel projet politique pour Mark Zuckerberg, possible prétendant à la Maison-Blanche ?

BigDataFr recommande : Quel projet politique pour Mark Zuckerberg, possible prétendant à la Maison-Blanche ? […] A quoi ressemblerait une présidence de Mark Zuckerberg à la tête des Etats-Unis ? Même si le patron de Facebook nie catégoriquement briguer la Maison-Blanche, il est passé maître dans l’art d’entretenir le doute sur sa possible entrée en […]

[arXiv – Ariane Carrance] BigDataFr recommends: Uniform random colored complexes

BigDataFr recommends: Uniform random colored complexes […] We present here random distributions on (D+1)-edge-colored, bipartite graphs with a fixed number of vertices 2p. These graphs are dual to D-dimensional orientable colored complexes. We investigate the behavior of quantities related to those random graphs, such as their number of connected components or the number of vertices […]

[Analyticsvidhya] BigDataFr recommends: 10 Advanced Deep Learning Architectures Data Scientists Should Know!

BigDataFr recommends: 10 Advanced Deep Learning Architectures Data Scientists Should Know! Introduction […] It is becoming very hard to stay up to date with recent advancements happening in deep learning. Hardly a day goes by without a new innovation or a new application of deep learning coming by. However, most of these advancements are hidden […]