DAI: How Pre-computation Speeds up Data Analysis

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Performance-critical industrial applications, including large-scale program, network, and distributed system analyses, are increasingly reliant on recursive queries for data analysis. Yet traditional relational algebra-based query optimization techniques d ...

Combined passive ultrasonic (US) stress wave [better known as acoustic emission (AE)] and active US stress wave monitoring has been shown to provide a more holistic picture of ongoing fracture processes, damage progression, as well as slowly occurring agin ...

Quantifying joint range of motion (RoM), the reachable poses at a joint, has many applications in research and clinical care. Joint RoM measurements can be used to investigate the link between form and function in extant and extinct animals, to diagnose mu ...

Federated learning (FL) is a machine learning setting where many clients (e.g., mobile devices or whole organizations) collaboratively train a model under the orchestration of a central server (e.g., service provider), while keeping the training data decen ...

Amid a data revolution that is transforming industries around the globe, computing systems have undergone a paradigm shift where many applications are scaled out to run on multiple computers in a computing cluster. As the storage and processing capabilitie ...

Modern applications accumulate data at an exponentially increasing rate and traditional database systems struggle to keep up. Decision support systems used in industry, rely heavily on data analysis, and require real-time responses irrespective of data siz ...

With large-scale simulations of increasingly detailed models and improvement of data acquisition technologies, massive amounts of data are easily and quickly created and collected. Traditional systems require indexes to be built before analytic queries can ...

Although privacy is generally considered to be the right of an individual or group to control information about themselves, such a right has become challenging to protect in the digital era, this is exemplified by the case of cloud-based genomic computing. ...

Third party applications work on top of existing platforms that host users’ data. Although these apps access this data to provide users with specific services, they can also use it for monetization or profiling purposes. In practice, there is a significant ...

Since the public release of Planck data, several attempts have been made to explain the observed small tensions with other data sets, most of them involving an extension of the Lambda cold dark matter (Lambda CDM) model. We try here an alternative approach ...

As the number of sensors that pervade our lives increases (e.g., environmental sensors, phone sensors, etc.), the eﬃcient management of massive amount of sensor data is becoming increasingly important. The inﬁnite nature of sensor data poses a serious chal ...

Manifold models provide low-dimensional representations that are useful for processing and analyzing data in a transformation-invariant way. In this paper, we study the problem of learning smooth pattern transformation manifolds from image sets that are ob ...

We have developed a method to analyze in detail, translocation events providing a novel and flexible tool for data analysis of nanopore experiments. Our program, called OpenNanopore, is based on the cumulative sums algorithm (CUSUM algorithm). This algorit ...

The work presented in this thesis deals with several problems met in information retrieval (IR), task which one can summarise as identifying, in a collection of "documents", a subset of documents carrying a sought information, i.e.. relevant for a request ...

DAI: How Pre-computation Speeds up Data Analysis

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Adaptive Recursive Query Optimization

Combined Passive and Active Ultrasonic Stress Wave Monitoring of Concrete Structures: An Overview of Data Analysis Techniques and Their Applications and Limitations

Spherical frame projections for visualising joint range of motion, and a complementary method to capture mobility data

Advances and Open Problems in Federated Learning

An Architecture for Load Balance in Computer Cluster Applications

Timely and cost-efficient data exploration through adaptive tuning

QUASII: QUery-Aware Spatial Incremental Index

On Secure Cloud Computing for Genomic Data: From Storage to Analysis

Data-Driven Privacy Indicators

Scalable Exploration of Spatial Data in Large-Scale Scientific Simulations

Separate constraints on early and late cosmology

Efficient Indexing and Query Processing of Model-View Sensor Data in the Cloud

Learning Smooth Pattern Transformation Manifolds

Fast and automatic processing of multi-level events in nanopore translocation experiments

Exploitation de connaissances sémantiques externes dans les représentations vectorielles en recherche documentaire