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A Comparative Analysis of Tools & Task Types for Measuring Computational Problem-Solving

Related publications (44)

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Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Paul Scharnhorst

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

EPFL2024

Attenuated Self-Interference Synchrophasor Estimation: the SOGI Interpolated DFT

Mario Paolone, Cesar Garcia Veloso

In this paper, a synchrophasor estimation (SE) algorithm is presented to simultaneously comply with the requirements for the P and M phasor measurement unit (PMU) performance classes. The method employs a second-order generalized integrator (SOGI) quadratu ...

IEEE2023

Mediating Computational Thinking Through Educational Robotics In Primary School

Morgane Solène Denise Chevalier

Nowadays, computational thinking (CT) is considered a skill to be taught. While educational robotics (ER) appears promising to foster students' CT, operational CT frameworks and explicit guidance in ER are lacking. This thesis thus proposes to understand h ...

EPFL2022

Computation Of A 30750-Bit Binary Field Discrete Logarithm

Arjen Lenstra, Robert Granger, Thorsten Kleinjung, Benjamin Pierre Charles Wesolowski

This paper reports on the computation of a discrete logarithm in the finite field F-230750, breaking by a large margin the previous record, which was set in January 2014 by a computation in F-29234. The present computation made essential use of the elimina ...

AMER MATHEMATICAL SOC2021

FANOK: Knockoffs in Linear Time

Quentin Rebjock

We describe a series of algorithms that efficiently implement Gaussian model-X knockoffs to control the false discovery rate on large-scale feature selection problems. Identifying the knockoff distribution requires solving a large-scale semidefinite progra ...

SIAM PUBLICATIONS2021

A Complexity Analysis Approach for Model-based System Engineering

Dimitrios Kyritsis, Jinzhi Lu, Xiaochen Zheng, Jinwei Chen

With the increasing complexity of the highly engineered products, Model-based Systems Engineering (MBSE) is proposed to support the complexity management of the product development. As the basic of complexity management, complexity analysis is used to meas ...

IEEE2020

A Primer on Motion Capture with Deep Learning: Principles, Pitfalls, and Perspectives

Alexander Mathis, Mackenzie Mathis, Steffen Schneider, Jessy Lauer

Extracting behavioral measurements non-invasively from video is stymied by the fact that it is a hard computational problem. Recent advances in deep learning have tremendously advanced our ability to predict posture directly from videos, which has quickly ...

2020

String Matching: Communication, Circuits, and Learning

Mika Tapani Göös

String matching is the problem of deciding whether a given n-bit string contains a given k-bit pattern. We study the complexity of this problem in three settings. - Communication complexity. For small k, we provide near-optimal upper and lower bounds on th ...

Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik GmbH, Wadern/Saarbruecken, Germany2019

Stable Fractional Matchings

Aris Filos Ratsikas

We study a generalization of the classical stable matching problem that allows for cardinal preferences (as opposed to ordinal) and fractional matchings (as opposed to integral). After observing that, in this cardinal setting, stable fractional matchings c ...

2019

Stable Fractional Matchings

Aris Filos Ratsikas

ASSOC COMPUTING MACHINERY2019