Results 21 to 30 of about 291 (165)
Some Results about the Contractions and the Pendant Pairs of a Submodular System [PDF]
Sahand Communications in Mathematical Analysis, 2019 Submodularity is an important property of set functions with deep theoretical results and various applications. Submodular systems appear in many applicable area, for example machine learning, economics, computer vision, social science, game theory ...
Saeid Hanifehnezhad, Ardeshir Dolati
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Algorithmica, 2012 We initiate the study of property testing of submodularity on the boolean hypercube. Submodular functions come up in a variety of applications in combinatorial optimization. For a vast range of algorithms, the existence of an oracle to a submodular function is assumed.
C. Seshadhri 0001, Jan Vondrák
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Team Composition in PES2018 Using Submodular Function Optimization
IEEE Access, 2019 With the development of computer game technologies, gameplay becomes very realistic in many sports games, therefore providing appealing play experience to game players.
Yifeng Zeng +3 more
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Discussiones Mathematicae - General Algebra and Applications, 2002 A lattice \(L\) of equivalence relations on a set \(A\neq \emptyset\) is called \(k\)-submodular \((k\geqq 2\) being a positive integer) if for all \(\theta, \phi, \psi \in L\) with \(\theta \subseteq \psi\) the condition \((\theta,\phi,\theta \dots)\cap \psi\subseteq \theta \vee (\phi\vee \psi)\) (where in the brackets on the left side there are \(k\)
Chajda, Ivan, Halaš, Radomír
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CoRR, 2018 This short article aims at demonstrate that the Intersection over Union (or Jaccard index) is not a submodular function. This mistake has been made in an article which is cited and used as a foundation in another article. The Intersection of Union is widely used in machine learning as a cost function especially for imbalance data and semantic ...
Tanguy Kerdoncuff, Rémi Emonet
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Continuous Submodular Maximization: Beyond DR-Submodularity
CoRR, 2020 19 ...
Moran Feldman, Amin Karbasi
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Greedy approximations for minimum submodular cover with submodular cost [PDF]
Computational Optimization and Applications, 2009 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Peng-Jun Wan +3 more
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Improved algorithms for submodular function minimization and submodular flow [PDF]
Proceedings of the thirty-second annual ACM symposium on Theory of computing, 2000 Very recently, two groups of researchers independently developed the first combinatorial, strongly polynomial-time algorithms for submodular function minimization (Iwata, Fleischer, Fujishige; and Schrijver). In this paper, we improve on these algorithms and show that the ideas generated in the design of these algorithms are helpful in other contexts ...
Lisa Fleischer, Satoru Iwata 0001
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On Submodular Contextual Bandits
CoRR, 2021 We consider the problem of contextual bandits where actions are subsets of a ground set and mean rewards are modeled by an unknown monotone submodular function that belongs to a class $\mathcal{F}$. We allow time-varying matroid constraints to be placed on the feasible sets.
Dean P. Foster, Alexander Rakhlin
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Feature Selection for Supervised Learning and Compression
Applied Artificial Intelligence, 2022 Supervised feature selection aims to find the signals that best predict a target variable. Typical approaches use measures of correlation or similarity, as seen in filter methods, or predictive power in learned models, as seen in wrapper methods. In both
Phillip Taylor +4 more
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