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HyperLogLog: Exponentially Bad in Adversarial Settings

Mathilde Aliénor Raynal

Computing the count of distinct elements in large data sets is a common task but naive approaches are memory-expensive. The HyperLogLog (HLL) algorithm (Flajolet et al., 2007) estimates a data set's cardinality while using significantly less memory than a ...

IEEE COMPUTER SOC2022

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

The Confidence Database

Nathan Quentin Faivre, Inaki Asier Iturrate Gil, Michael Eric Anthony Pereira, Xiao Hu, Caroline Peters

Understanding how people rate their confidence is critical for the characterization of a wide range of perceptual, memory, motor and cognitive processes. To enable the continued exploration of these processes, we created a large database of confidence stud ...

NATURE PUBLISHING GROUP2020

Timely and cost-efficient data exploration through adaptive tuning

Matthaios Alexandros Olma

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 ...

EPFL2019

In the problem of coded caching for media delivery, two separate coding opportunities have been identified. The first opportunity is a multi-user advantage and crucially hinges on a public broadcast link in the delivery phase. This has been explored in a p ...

IEEE2019

Caching and Distributed Storage

Saeid Sahraei

A simple task of storing a database or transferring it to a different point via a communication channel turns far more complex as the size of the database grows large. Limited bandwidth available for transmission plays a central role in this predicament. I ...

EPFL2018

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Nearest neighbor searching of large databases in high-dimensional spaces is inherently difficult due to the curse of dimensionality. A flavor of approximation is, therefore, necessary to practically solve the problem of nearest neighbor search. In this pap ...

ASSOC COMPUTING MACHINERY2018

Dictionary Compression in Point Cloud Data Management

Anastasia Ailamaki, Mirjana Pavlovic

Nowadays, massive amounts of point cloud data can be collected thanks to advances in data acquisition and processing technologies like dense image matching and airborne LiDAR (Light Detection and Ranging) scanning. With the increase in volume and precision ...

2017

Toward timely, predictable and cost-effective data analytics

Renata Borovica-Gajic

Modern industrial, government, and academic organizations are collecting massive amounts of data at an unprecedented scale and pace. The ability to perform timely, predictable and cost-effective analytical processing of such large data sets in order to ext ...

EPFL2016

Distinguishing Crowd Dynamics in Small Teams: A Crowdsourcing Exercise in Higher Education

Christopher Tucci, Gianluigi Viscusi

Folk wisdom usually takes the number of participants as an often necessary and sufficient condition for identifying a crowd. This assumption has diffused among academics interested in crowdsourcing and collective intelligence as well. Yet, consider 50 peop ...

2016