Results 21 to 30 of about 8,591 (298)
Unified Greedy Approximability beyond Submodular Maximization
SIAM Journal on Discrete Mathematics, 2022 We consider classes of objective functions of cardinality constrained maximization problems for which the greedy algorithm guarantees a constant approximation. We propose the new class of $γ$-$α$-augmentable functions and prove that it encompasses several important subclasses, such as functions of bounded submodularity ratio, $α$-augmentable functions,
Yann Disser, David Weckbecker
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Lebesgue constants for Chebyshev thresholding greedy algorithms
Journal of Inequalities and Applications, 2018 We investigate the efficiency of Chebyshev Thresholding Greedy Algorithm (CTGA) for an n-term approximation with respect to general bases in a Banach space. We show that the convergence property of CTGA is better than TGA for non-quasi-greedy bases. Then
Chunfang Shao, Peixin Ye
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A Comparison between Fixed-Basis and Variable-Basis Schemes for Function Approximation and Functional Optimization [PDF]
, 2012 Fixed-basis and variable-basis approximation schemes are compared for the problems of function approximation and functional optimization (also known as infinite programming).
Gnecco, Giorgio +3 more
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Submodular stochastic probing on matroids [PDF]
, 2014 In a stochastic probing problem we are given a universe E, where each element e in E is active independently with probability p in [0,1], and only a probe of e can tell us whether it is active or not. On this universe we execute a process that one by one
Sviridenko, Maxim +5 more
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Regularized Submodular Maximization With a
IEEE Access, 2023 With the development of the Internet and the emergence of various social-media platforms, designing approximation algorithms for optimization problems such as the influence maximization in social networks has received widespread attention.
Qingqin Nong, Zhijia Guo, Suning Gong
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Greedy Approximation in Convex Optimization [PDF]
Constructive Approximation, 2015 We study sparse approximate solutions to convex optimization problems. It is known that in many engineering applications researchers are interested in an approximate solution of an optimization problem as a linear combination of elements from a given system of elements. There is an increasing interest in building such sparse approximate solutions using
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Adaptive Piecewise Poly-Sinc Methods for Ordinary Differential Equations
Algorithms, 2022 We propose a new method of adaptive piecewise approximation based on Sinc points for ordinary differential equations. The adaptive method is a piecewise collocation method which utilizes Poly-Sinc interpolation to reach a preset level of accuracy for the
Omar Khalil +3 more
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Clustering Affine Subspaces: Algorithms and Hardness [PDF]
, 2012 We study a generalization of the famous k-center problem where each object is an affine subspace of dimension Δ, and give either the first or significantly improved algorithms and hardness results for many combinations of parameters.
Lee, Euiwoong
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A Functional Characterization of Almost Greedy and Partially Greedy Bases in Banach Spaces
Mathematics, 2021 In 2003, S. J. Dilworth, N. J. Kalton, D. Kutzarova and V. N. Temlyakov introduced the notion of almost greedy (respectively partially greedy) bases. These bases were characterized in terms of quasi-greediness and democracy (respectively conservativeness)
Pablo Manuel Berná, Diego Mondéjar
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Reduced Basis Approximation for a Spatial Lotka-Volterra Model
Mathematics, 2022 We construct a reduced basis approximation for the solution to a system of nonlinear partial differential equations describing the temporal evolution of two populations following the Lotka-Volterra law. The first population’s carrying capacity contains a
Peter Rashkov
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