191 research outputs found
LIPIcs, Volume 251, ITCS 2023, Complete Volume
LIPIcs, Volume 251, ITCS 2023, Complete Volum
LIPIcs, Volume 261, ICALP 2023, Complete Volume
LIPIcs, Volume 261, ICALP 2023, Complete Volum
Conflict Checkable and Decodable Codes and Their Applications
Let be an error-correcting code over a large alphabet of block length , and assume that, a possibly corrupted, codeword is distributively stored among servers where the th entry is being held by the th server. Suppose that every pair of servers publicly announce whether the corresponding coordinates are ``consistent\u27\u27 with some legal codeword or ``conflicted\u27\u27. What type of information about can be inferred from this consistency graph? Can we check whether errors occurred and if so, can we find the error locations and effectively decode? We initiate the study of conflict-checkable and conflict-decodable codes and prove the following main results:
(1) (Almost-MDS conflict-checkable codes:) For every distance , there exists a code that supports conflict-based error-detection whose dimension almost achieves the singleton bound, i.e., . Interestingly, the code is non-linear, and we give some evidence that suggests that this is inherent. Combinatorially, this yields an -partite graph over that contains cliques of size whose pair-wise intersection is at most vertices, generalizing a construction of Alon (Random Struct. Algorithms, \u2702) that achieves a similar result for the special case of triangles ().
(2) (Conflict Decodable Codes below half-distance:) For every distance there exists a linear code that supports conflict-based error-decoding up to half of the distance. The code\u27s dimension ``half-meets\u27\u27 the singleton bound, i.e., , and we prove that this bound is tight for a natural class of such codes. The construction is based on symmetric bivariate polynomials and is rooted in the literature on verifiable secret sharing (Ben-Or, Goldwasser and Wigderson, STOC \u2788; Cramer, Damgård, and Maurer, EUROCRYPT \u2700).
(3) (Robust Conflict Decodable Codes:) We show that the above construction also satisfies a non-trivial notion of robust decoding/detection even when the number of errors is unbounded and up to of the servers are Byzantine and may lie about their conflicts. The resulting conflict-decoder runs in exponential time in this case, and we present an alternative construction that achieves quasipolynomial complexity at the expense of degrading the dimension to . Our construction is based on trilinear polynomials, and the algorithmic result follows by showing that the induced conflict graph is structured enough to allow efficient recovery of a maximal vertex cover.
As an application of the last result, we present the first polynomial-time statistical two-round Verifiable Secret Sharing (resp., three-round general MPC protocol) that remains secure in the presence of an active adversary that corrupts up to of the parties. We can upgrade the resiliency threshold to , which is known to be optimal in this setting, at the expense of increasing the computational complexity to be quasipolynomial. Previous solutions (Applebaum, Kachlon, and Patra, TCC\u2720) suffered from an exponential-time complexity even when the adversary corrupts only of the parties
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Beyond Worst-Case Analysis for Sequential Decision Making
Traditionally, algorithms have been evaluated through worst-case analysis, where the input is presumed to take its worst possible configuration. However, in many real-world settings, the data is not adversarially constructed and, on the contrary, exhibits some recognizable patterns. This often leads worst-case guarantees to be poor indicators of algorithms' performance. To overcome this limitation, a growing body of work on Beyond Worst-Case analysis has recently emerged.
In this thesis, we are concerned with sequential decision-making problems, where an agent must take successive decisions over multiple time steps without knowing in advance the forthcoming input. Examples of such settings include ride-sharing, online retail or job scheduling. Motivated by the unprecedented surge of data in these domains, which may help to overcome worst-case barriers by allowing to predict at least partially the future, we explore three distinct frameworks for Beyond Worst-Case analysis of sequential decision-making: (i) semi-random models, (ii) parametric models, and (iii) algorithms with predictions. While they all pursue the same objective — using previously collected data to provide stronger theoretical guarantees —, these frameworks mainly differ in the way the data is utilized. We examine each of them separately and present novel results for five different online optimization problems: minimum cost matching, assortment optimization (with and without inventory constraints), pricing and scheduling
LIPIcs, Volume 274, ESA 2023, Complete Volume
LIPIcs, Volume 274, ESA 2023, Complete Volum
Technology and Management Applied in Construction Engineering Projects
This book focuses on fundamental and applied research on construction project management. It presents research papers and practice-oriented papers. The execution of construction projects is specific and particularly difficult because each implementation is a unique, complex, and dynamic process that consists of several or more subprocesses that are related to each other, in which various aspects of the investment process participate. Therefore, there is still a vital need to study, research, and conclude the engineering technology and management applied in construction projects. This book present unanimous research approach is a result of many years of studies, conducted by 35 well experienced authors. The common subject of research concerns the development of methods and tools for modeling multi-criteria processes in construction engineering
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Examining university student satisfaction and barriers to taking online remote exams
Recent years have seen a surge in the popularity of online exams at universities, due to the greater convenience and flexibility they offer both students and institutions. Driven by the dearth of empirical data on distance learning students' satisfaction levels and the difficulties they face when taking online exams, a survey with 562 students at The Open University (UK) was conducted to gain insights into their experiences with this type of exam. Satisfaction was reported with the environment and exams, while work commitments and technical difficulties presented the greatest barriers. Gender, race and disability were also associated with different levels of satisfaction and barriers. This study adds to the increasing number of studies into online exams, demonstrating how this type of exam can still have a substantial effect on students experienced in online learning systems and
technologies
Energy Data Analytics for Smart Meter Data
The principal advantage of smart electricity meters is their ability to transfer digitized electricity consumption data to remote processing systems. The data collected by these devices make the realization of many novel use cases possible, providing benefits to electricity providers and customers alike. This book includes 14 research articles that explore and exploit the information content of smart meter data, and provides insights into the realization of new digital solutions and services that support the transition towards a sustainable energy system. This volume has been edited by Andreas Reinhardt, head of the Energy Informatics research group at Technische Universität Clausthal, Germany, and Lucas Pereira, research fellow at Técnico Lisboa, Portugal
LIPIcs, Volume 244, ESA 2022, Complete Volume
LIPIcs, Volume 244, ESA 2022, Complete Volum
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