Results 31 to 40 of about 9,676,389 (199)
Effect of Objective Function on Data-Driven Greedy Sparse Sensor Optimization
IEEE Access, 2021 The problem of selecting an optimal set of sensors estimating a high-dimensional data is considered. Objective functions based on D-, A-, and E-optimality criteria of optimal design are adopted to greedy methods, that maximize the determinant, minimize ...
Kumi Nakai +4 more
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Parallelizing greedy for submodular set function maximization in matroids and beyond [PDF]
Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, 2019 We consider parallel, or low adaptivity, algorithms for submodular function maximization. This line of work was recently initiated by Balkanski and Singer and has already led to several interesting results on the cardinality constraint and explicit packing constraints.
Chandra Chekuri, Kent Quanrud
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Multimodal Hierarchical Dirichlet Process-Based Active Perception by a Robot
Frontiers in Neurorobotics, 2018 In this paper, we propose an active perception method for recognizing object categories based on the multimodal hierarchical Dirichlet process (MHDP). The MHDP enables a robot to form object categories using multimodal information, e.g., visual, auditory,
Tadahiro Taniguchi +2 more
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Maximizing submodular set function with connectivity constraint: Theory and application to networks [PDF]
2013 Proceedings IEEE INFOCOM, 2013 In this paper, we investigate the wireless network deployment problem, which seeks the best deployment of a given limited number of wireless routers. We found that many goals for network deployment, such as maximizing the number of covered users or areas, or the total throughput of the network, can be modelled with the submodular set function ...
Tung-Wei Kuo +2 more
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Generalized Budgeted Submodular Set Function Maximization [PDF]
, 2018 In this paper we consider a generalization of the well-known budgeted maximum coverage problem. We are given a ground set of elements and a set of bins. The goal is to find a subset of elements along with an associated set of bins, such that the overall ...
Velaj, Yllka +7 more
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Submodularity of a Set Label Disagreement Function
CoRR, 2013 A set label disagreement function is defined over the number of variables that deviates from the dominant label. The dominant label is the value assumed by the largest number of variables within a set of binary variables. The submodularity of a certain family of set label disagreement function is discussed in this manuscript. Such disagreement function
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Shaping Level Sets with Submodular Functions
CoRR, 2010 We consider a class of sparsity-inducing regularization terms based on submodular functions. While previous work has focused on non-decreasing functions, we explore symmetric submodular functions and their \lova extensions. We show that the Lovasz extension may be seen as the convex envelope of a function that depends on level sets (i.e., the set of ...
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You Can Recharge With Detouring: Optimizing Placement for Roadside Wireless Charger
IEEE Access, 2018 Wireless energy transfer technologies have played an important role in the development of Internet of Things. Most of the previous studies focus on scheduling mobile chargers efficiently for rechargeable sensor nodes.
Xunpeng Rao +6 more
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Applied Sciences, 2019 Competitive Influence Maximization ( CIM ) problem, which seeks a seed set nodes of a player or a company to propagate their product’s information while at the same time their competitors are conducting similar strategies, has been paid much ...
Canh V. Pham +3 more
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Capturing Complementarity in Set Functions by Going Beyond Submodularity/Subadditivity
CoRR, 2018 ITCS2019
Wei Chen 0013 +2 more
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