On finding approximate nearest neighbours in a set of compressible signals

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Scalable Multi-Query Execution using Reinforcement Learning

Anastasia Ailamaki, Panagiotis Sioulas

The growing demand for data-intensive decision support and the migration to multi-tenant infrastructures put databases under the stress of high analytical query load. The requirement for high throughput contradicts the traditional design of query-at-a-time ...

Association for Computing Machinery2021

Representation Learning for Multi-relational Data

Eda Bayram

Recent years have witnessed a rise in real-world data captured with rich structural information that can be better depicted by multi-relational or heterogeneous graphs. However, research on relational representation learning has so far mostly focused on th ...

EPFL2021

Spectral Measurement and Classification in the Era of Big Data

Marilyne Andersen, Forrest Simon Webler

The measurement and classification of light is essential across many scientific disciplines. Devices used to measure light range from the highly precise scanning spectroradiometers to the more practical compact multichannel filter-array type imaging sensor ...

2021

Sparsest piecewise-linear regression of one-dimensional data

Michaël Unser, Julien René Fageot, Thomas Jean Debarre, Quentin Alain Denoyelle

We study the problem of one-dimensional regression of data points with total-variation (TV) regularization (in the sense of measures) on the second derivative, which is known to promote piecewise-linear solutions with few knots. While there are efficient a ...

Elsevier2021

System and methods for real time noninvasive estimation of cardiovascular parameters

Nikolaos Stergiopoulos, Vasiliki Bikia, Stamatia Zoi Pagoulatou

Systems and methods are provided for that use noninvasively measured physiologic parameters to predict in real time noninvasively unobservable cardiovascular parameters by employing a one-dimensional arterial tree numerical model calibrated with representa ...

2021

Worldwide performance evaluation of ground surface reflectance models

Christophe Ballif, Arttu Matias Tuomiranta

To improve the accuracy of bifacial gain estimation, recent radiative models of solar energy systems have abandoned the traditional assumption of isotropic ground-reflected radiance. However, surface reflectance itself is still commonly considered as a con ...

2021

Imputation of missing information in worldwide patent data

Gaétan Jean A de Rassenfosse

We present a general method for imputing missing information in the Worldwide Patent Statistical Database (PATSTAT) and make the resulting datasets publicly available. The PATSTAT database is the de facto standard for academic research using patent data. C ...

2021

A Real-time Synchrophasor Data Compression Method Using Singular Value Decomposition

Mario Paolone

The proliferation of phasor measurement units (PMUs) presents new challenges in archiving and processing large amounts of synchrophasor data which necessitates advanced data compression methods. This paper proposes a singular value decomposition (SVD)-base ...

2021

Holistic, Efficient, and Real-time Cleaning of Heterogeneous Data

Styliani Asimina Giannakopoulou

Data cleaning has become an indispensable part of data analysis due to the increasing amount of dirty data. Data scientists spend most of their time preparing dirty data before it can be used for data analysis. Existing solutions that attempt to automate t ...

EPFL2021

Propagation on Multi-relational Graphs for Node Regression

Eda Bayram

Recent years have witnessed a rise in real-world data captured with rich structural information that can be conveniently depicted by multi-relational graphs. While inference of continuous node features across a simple graph is rather under-studied by the c ...

Springer, Cham2022