Results 11 to 20 of about 89,468 (247)
Concept-based Summarization using Integer Linear Programming: From Concept Pruning to Multiple Optimal Solutions [PDF]
Conference on Empirical Methods in Natural Language Processing, 2015 International audienceIn concept-based summarization, sentence selection is modelled as a budgeted maximum coverage problem. As this problem is NP-hard, pruning low-weight concepts is required for the solver to find optimal solutions efficiently.
Boudin, Florian +2 more
core +5 more sources
Coverage, Matching, and Beyond: New Results on Budgeted Mechanism Design
Workshop on Internet and Network Economics, 2016 We study a type of reverse (procurement) auction problems in the presence of budget constraints. The general algorithmic problem is to purchase a set of resources, which come at a cost, so as not to exceed a given budget and at the same time maximize a ...
AA Ageev +6 more
core +2 more sources
Probability Learning based Tabu Search for the Budgeted Maximum Coverage Problem [PDF]
Expert systems with applications, 2020 Knapsack problems are classic models that can formulate a wide range of applications. In this work, we deal with the Budgeted Maximum Coverage Problem (BMCP), which is a generalized 0-1 knapsack problem.
Liwen Li +3 more
semanticscholar +1 more source
Budgeted Thompson Sampling for IRS Enabled WiGig Relaying
Electronics, 2023 Intelligent reconfigurable surface (IRS) is a competitive relaying technology to widen the WiGig coverage range, as it offers an effective means of addressing blocking issues. However, selecting the optimal IRS relay for maximum attainable data rate is a
Sherief Hashima +3 more
semanticscholar +1 more source
Observer Placement for Source Localization: The Effect of Budgets and Transmission Variance [PDF]
, 2016 When an epidemic spreads in a network, a key question is where was its source, i.e., the node that started the epidemic. If we know the time at which various nodes were infected, we can attempt to use this information in order to identify the source ...
Celis, L. Elisa +2 more
core +2 more sources
A Nested Genetic Algorithm for Explaining Classification Data Sets with Decision Rules [PDF]
arXiv.org, 2022 Our goal in this paper is to automatically extract a set of decision rules (rule set) that best explains a classification data set. First, a large set of decision rules is extracted from a set of decision trees trained on the data set. The rule set should
P. Matt +4 more
semanticscholar +1 more source
Sticky Seeding in Discrete-Time Reversible-Threshold Networks [PDF]
, 2016 When nodes can repeatedly update their behavior (as in agent-based models from computational social science or repeated-game play settings) the problem of optimal network seeding becomes very complex.
Spencer, Gwen
core +3 more sources
Maximum Betweenness Centrality: Approximability and Tractable Cases [PDF]
Workshop on Algorithms and Computation, 2010 The MAXIMUM BETWEENNESS CENTRALITY problem (MBC) can be defined as follows. Given a graph find a k-element node set C that maximizes the probability of detecting communication between a pair of nodes s and t chosen uniformly at random. It is assumed that
Martin Fink, J. Spoerhase
semanticscholar +1 more source
A Constant Approximation for Colorful k-Center [PDF]
, 2019 In this paper, we consider the colorful k-center problem, which is a generalization of the well-known k-center problem. Here, we are given red and blue points in a metric space, and a coverage requirement for each color.
Bandyapadhyay, Sayan +3 more
core +2 more sources
Advanced Engineering Materials, EarlyView.Do not let thermal drift and instrument artifacts deceive high‐temperature nanoindentation results. We compare classical Oliver–Pharr and automatic image recognition analyses across steels and a Ni alloy to quantify these effects. Accounting for artifacts reveals systematic softening with temperature, while Cr and Ni additions boost resistance ...
Velislava Yonkova +2 more
wiley +1 more source