BigDatFr recommends: Mapping Big Data into Knowledge Space with Cognitive Cyber-Infrastructure ‘Big data research has attracted great attention in science, technology, industry and society. It is developing with the evolving scientific paradigm, the fourth industrial revolution, and the transformational innovation of technologies. However, its nature and fundamental challenge have not been recognized, and its own […]
Innovation
[arXiv] BigDataFr recommends: A Flexible Coordinate Descent Method for Big Data Applications #datascientist #machinelearning
BigDatafr recommends: A Flexible Coordinate Descent Method for Big Data Applications ‘In this paper we present a novel randomized block coordinate descent method for the minimization of a convex composite objective function. The method uses (approximate) partial second-order (curvature) information, so that the algorithm performance is more robust when applied to highly nonseparable or ill […]
[arXiv] BigDataFr recommends: Experimental Study of the Cloud Architecture Selection for Effective Big Data Processing
BigDataFr recommends: Experimental Study of the Cloud Architecture Selection for Effective Big Data Processing ‘Big data dictate their requirements to the hardware and software. Simple migration to the cloud data processing, while solving the problem of increasing computational capabilities, however creates some issues: the need to ensure the safety, the need to control the quality […]
[arXiv] BigDataFr recommends: Big Data Analytics in Bioinformatics – A Machine Learning Perspective #machine-learning
BigDataFr recommends: Big Data Analytics in Bioinformatics – A Machine Learning Perspective ‘Bioinformatics research is characterized by voluminous and incremental datasets and complex data analytics methods. The machine learning methods used in bioinformatics are iterative and parallel. These methods can be scaled to handle big data using the distributed and parallel computing technologies. Usually big […]
[MIT Technology Review] BigDataFr recommends: Deep Learning Machine Beats Humans in IQ Test
BigDataFr recommends: Deep Learning Machine Beats Humans in IQ Test ‘Computers have never been good at answering the type of verbal reasoning questions found in IQ tests. Now a deep learning machine unveiled in China is changing that. ‘ Read more Emerging Technology From the arXiv Source: technologyreview.com
[arXiv] BigDataFr recommends: Predicting Regional Economic Indices using Big Data of Individual Bank Card Transactions #machine learning #datascientist
BigDataFr recommends: Predicting Regional Economic Indices using Big Data of Individual Bank Card Transactions ‘For centuries quality of life was a subject of studies across different disciplines. However, only with the emergence of a digital era, it became possible to investigate this topic on a larger scale. Over time it became clear that quality of […]
[arXiv] BigDataFr recommends: Behaviour of ABC for Big Data #datascientist #machinelearning
BigDataFr recommends: Behaviour of ABC for Big Data ‘Many statistical applications involve models that it is difficult to evaluate the likelihood, but relatively easy to sample from, which is called intractable likelihood. Approximate Bayesian computation (ABC) is a useful Monte Carlo method for inference of the unknown parameter in the intractable likelihood problem under Bayesian […]
[arXiv] BigDataFr recommends: Benchmarking Big Data Systems – State-of-the-Art and Future Directions #datascientist #machinelearning
BigDataFr recommends: Benchmarking Big Data Systems – State-of-the-Art and Future Directions ‘The great prosperity of big data systems such as Hadoop in recent years makes the benchmarking of these systems become crucial for both research and industry communities. The complexity, diversity, and rapid evolution of big data systems gives rise to various new challenges about […]
[arXiv] BigDataFr recommends: Identifying Dwarfs Workloads in Big Data Analytics #datascientist #machinelearning
BigDataFr recommends: Identifying Dwarfs Workloads in Big Data Analytics ‘Big data benchmarking is particularly important and provides applicable yardsticks for evaluating booming big data systems. However, wide coverage and great complexity of big data computing impose big challenges on big data benchmarking. How can we construct a benchmark suite using a minimum set of units […]
[arXiv] BigDataFr recommends: Online Updating of Statistical Inference in the Big Data Setting
BigDataFr recommends: Online Updating of Statistical Inference in the Big Data Setting ‘We present statistical methods for big data arising from online analytical processing, where large amounts of data arrive in streams and require fast analysis without storage/access to the historical data. In particular, we develop iterative estimating algorithms and statistical inferences for linear models […]