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BILEVEL OPTIMIZATION PROBLEMS OF DISTRIBUTION OF INTERBUDGETARY TRANSFERS UNDER GIVEN LIMITATIONS

CYBERNETICS AND SYSTEMS ANALYSIS 2019年第6期55卷 905-913页

作者： Sergienko, I. V. Semenova, N. V. Semenov, V. V. Natl Acad Sci Ukraine VM Glushkov Inst Cybernet Kiev Ukraine

The problems of optimal distribution of transfers within given budget limitations are formulated and analyzed. The mathematical model is presented as a bilevel linear optimization problem that contains linear problems of integer optimization at the lower level. Both optimistic and pessimistic versions of the problem are considered. Far the approximate solution of optimistic version, the algorithm of finding local solutions for parametric lower-level integer programming problems on the basis of the method of directing neighborhoods is proposed. The auxiliary integer progrannning problem with Boolean variables of a higher level is solved bused on local algorithms.

关键词： bilevel optimization problem integer optimization parametric programming Boolean variables local algorithm

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A self-adaptive local metric learning method for classification

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PATTERN RECOGNITION 2019年 96卷 106994-000页

作者： Taheri, Mahsa Moslehi, Zahra Mirzaei, Abdolreza Safayani, Mehran Isfahan Univ Technol Dept Elect & Comp Engn Esfahan *** Iran

Measuring distance among data point pairs is a necessary step among numerous counts of algorithms in machine learning, pattern recognition and data mining. In the local perspective, the emphasis of all existing supervised metric learning algorithms is to shrink similar data points and to separate dissimilar ones in the local neighborhoods. This provides learning more appropriate distance metric in dealing with the within-class multi modal data. In this article, a new supervised local metric learning method named Self-Adaptive local Metric Learning Method (SA-LM2) has been proposed. The contribution of this method is in five aspects. First, in this method, learning an appropriate metric and defining the radius of local neighborhood are integrated in a joint formulation. Second, unlike the traditional approaches, SA-LM2 learns the parameter of local neighborhood automatically thorough its formulation. As a result, it is a parameter free method, where it does not require any parameters that would need to be tuned. Third, SA-LM2 is formulated as a SemiDefinite Program (SDP) with a global convergence guarantee. Fourth, this method does not need the similar set S, the focus here is on local areas' data points and their separation from dissimilar ones. Finally, results of SA-LM2 are less influenced by noisy input data points than the other compared global and local algorithms. Results obtained from different experiments indicate the outperformance of this algorithm over its counterparts. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Supervised metric learning Linear metric learning local algorithm Neighborhood learning Multimodal data

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How Well Do local algorithms Solve Semidefinite Programs? 2017

How Well Do Local Algorithms Solve Semidefinite Programs?

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49th Annual ACM-SIGACT Symposium on Theory of Computing (STOC)

作者： Fan, Zhou Montanari, Andrea Stanford Univ Dept Stat Stanford CA 94305 USA Stanford Univ Dept Elect Engn Stanford CA 94305 USA

ISBN: (纸本)9781450345286

Several probabilistic models from high-dimensional statistics and machine learning reveal an intriguing - and yet poorly understood-dichotomy. Either simple local algorithms succeed in estimating the object of interest, or even sophisticated semi-definite programming (SDP) relaxations fail. In order to explore this phenomenon, we study a classical SDP relaxation of the minimum graph bisection problem, when applied to Erdos-Renyi random graphs with bounded average degree d > 1, and obtain several types of results. First, we use a dual witness construction (using the so-called non-backtracking matrix of the graph) to upper bound the SDP value. Second, we prove that a simple local algorithm approximately solves the SDP to within a factor 2d(2)/(2d(2) + d - 1) of the upper bound. In particular, the local algorithm is at most 8/9 suboptimal, and 1 + O(1/d) suboptimal for large degree. We then analyze a more sophisticated local algorithm, which aggregates information according to the harmonic measure on the limiting Galton-Watson (GW) tree. The resulting lower bound is expressed in terms of the conductance of the GW tree and matches surprisingly well the empirically determined SDP values on large-scale Erdos-Renyi graphs. We finally consider the planted partition model. In this case, purely local algorithms are known to fail, but they do succeed if a small amount of side information is available. Our results imply quantitative bounds on the threshold for partial recovery using SDP in this model.

关键词： local algorithm semidefinite program relaxation non-backtracking spectrum community detection

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Dynamic Representations of Sparse Distributed Networks: A locality-Sensitive Approach 18

Dynamic Representations of Sparse Distributed Networks: A Lo...

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30th ACM Symposium on Parallelism in algorithms and Architectures (SPAA)

作者： Kaplan, Haim Solomon, Shay Tel Aviv Univ Tel Aviv Israel IBM Res TJ Watson Res Ctr New York NY USA

ISBN: (纸本)9781450357999

In 1999, Brodal and Fagerberg (BF) gave an algorithm for maintaining a low outdegree orientation of a dynamic uniformly sparse graph. Specifically, for a dynamic graph on n-vertices, with arboricity bounded by alpha at all times, the BF algorithm supports edge updates in O(log n) amortized update time, while keeping the maximum outdegree in the graph bounded by O(alpha). Such an orientation provides a basic data structure for uniformly sparse graphs, which found applications to a plethora of dynamic graph algorithms. A significant weakness of the BF algorithm is the possible temporary blowup of the maximum outdegree, following edge insertions. Although BF eventually reduces all outdegrees to O(alpha), some vertices may reach an outdegree of Omega(n) during the process, hence local memory usage at the vertices-an important quality measure in distributed systems-cannot be bounded. We show how to modify the BF algorithm to guarantee that the outdegrees of all vertices are bounded by O(alpha) at all times, without hurting any of its other properties, and present an efficient distributed implementation of the modified algorithm. This provides the first representation of distributed networks in which the local memory usage at vertices is bounded by the arboricity (which is essentially the average degree of the densest subgraph) rather than the maximum degree. For settings where there is no local memory constraints, one may take the temporary outdegree blowup to the extreme and allow a permanent outdegree blowup. This allows us to address the second significant weakness of the BF algorithm - its inherently global nature: An insertion of an edge (u, v) may trigger changes in the orientations of edges that are arbitrarily far away from u and v. We suggest an alternative local scheme, which does not guarantee any outdegree bound on the vertices, yet is just as efficient as the BF scheme for some applications. For example, we obtain a local dynamic algorithm for maintaining a

关键词： arboricity dynamic network local algorithm local memory

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local Digital algorithms Applied to Boolean Models

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SCANDINAVIAN JOURNAL OF STATISTICS 2017年第2期44卷 369-395页

作者： Hoerrmann, Julia Svane, Anne Marie Ruhr Univ Bochum Fac Math Bochum Germany Aarhus Univ Dept Math DK-8000 Aarhus C Denmark

We investigate the estimation of specific intrinsic volumes of stationary Boolean models by local digital algorithms;that is, by weighted sums of local configuration counts. We show that asymptotically unbiased estimators for the specific surface area or integrated mean curvature do not exist if the dimension is at least two or three, respectively. For three-dimensional stationary isotropic Boolean models, we derive asymptotically unbiased estimators for the specific surface area and integrated mean curvature. For a Boolean model with balls as grains, we even obtain an asymptotically unbiased estimator for the specific Euler characteristic.

关键词： Boolean model digital image local algorithm Miles formulae specific intrinsic volume

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Developing universal models for the prediction of physical quality in citrus fruits analysed on-tree using portable NIRS sensors

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BIOSYSTEMS ENGINEERING 2017年 153卷 140-148页

作者： Torres, Irina Perez-Marin, Dolores De la Haba, Maria-Jose Sanchez, Maria-Teresa Univ Cordoba Dept Bromathol & Food Technol Campus Rabanales E-14071 Cordoba Spain Univ Cordoba Dept Anim Prod Campus Rabanales E-14071 Cordoba Spain

The citrus sector seeks rapid, economical, environmentally-friendly and non-destructive technologies for monitoring external and internal changes in physical quality taking place in fruit during on-tree growth, thus allowing fruit quality to be evaluated at any stage of fruit development. The use of portable near-infrared spectroscopy (NIRS) sensors based on micro-electro-mechanical system (MEMS) technology, in conjunction with chemometric data treatment models, has already been studied for quality-control purposes in two citrus species: oranges and mandarins. The critical challenge is to develop robust and accurate universal models based on hundreds of highly heterogeneous citrus samples in order to design quality prediction models applicable to all fruits belonging to the genus Citrus, rather than models that can only be applied successfully to a single citrus species. This study evaluated and compared the performance of Modified Partial Least Squares (MPLS) and local regression algorithms for the prediction of major physical-quality parameters in all citrus fruits. Results showed that, while models developed using both linear (MPLS) and non-linear regression techniques (local) yielded promising results for the on-tree quality evaluation of citrus fruits, the local algorithm additionally increased the predictive capacity of models constructed for all the main parameters tested. These findings confirm that NIRS technology, used in conjunction with large databases and local regression strategies, increases the robustness of models for the on-tree prediction of citrus fruit quality;this will undoubtedly be of benefit to the citrus industry. (c) 2016 IAgrE. Published by Elsevier Ltd. All rights reserved.

关键词： NIRS Citrus Physical quality Universal models MPLS regression local algorithm

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Fragmentary Structures in Discrete Optimization Problems

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CYBERNETICS AND SYSTEMS ANALYSIS 2017年第6期53卷 931-936页

作者： Kozin, I. V. Maksyshko, N. K. Perepelitsa, V. A. Zaporizhzhya Natl Univ Zaporizhzhya Ukraine

The paper considers a combinatorial object (a fragmentary structure) and investigates the properties of this object. It is shown that a number of discrete optimization problems can be considered as optimization problems on a fragmentary structure. Optimization problem reduces to an unconditional combinatorial optimization problem on a set of permutations. Variants of algorithms to find approximate solutions for optimization problems of fragmentary structure are proposed.

关键词： discrete optimization fragmentary structure local algorithm evolutionary algorithm ant algorithm

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Freedom of speech for all critically ill patients: work in progress

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CRITICAL CARE 2017年第1期21卷 1-2页

作者： Tuinman, P. R. ten Hoorn, S. VU Univ Med Ctr Amsterdam Dept Intens Care Med & Res VUmc Intens Care REVIV Room ZH-7D-166De Boelelaan 1117POB 7057 NL-1007 MB Amsterdam Netherlands VU Univ Med Ctr Amsterdam Inst Cardiovasc Res VU ICaR VU Amsterdam Netherlands

See related Letter by Sutt et al., https://***/articles/10.1186/s13054-016-1588-7 and related Letter by Egbers et al., https://***/articles/10.1186/s13054-016-1587-8

关键词： local algorithm Speech Enhancement Cuff Deflation Simple Communication Intensive Care Unit Staff

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Short Paper: Structural Network Properties for local Planarization of Wireless Sensor Networks 15th

Short Paper: Structural Network Properties for Local Planari...

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15th International Conference on Ad-Hoc Networks and Wireless (ADHOC-NOW)

作者： Neumann, Florentin Estevao, Daniel Vivas Ockenfeld, Frank Radak, Jovan Frey, Hannes Univ Koblenz Landau Inst Comp Sci Koblenz Germany

ISBN: (纸本)9783319405094;9783319405087

Network graphs satisfying redundancy and coexistence can be planarized by means of local algorithms without making assumptions on the nodes' communication ranges. We generalize these properties to k-weak and k-strong coexistence and redundancy. Subsequently, we give empirical evidence that these properties are present in simulated wireless sensor networks as well as in actual testbed deployments, especially if looking at the graph's c-hop clustered overlay representations, for c <= 2.

关键词： WSN Planarization local algorithm Geometric graph Redundancy Coexistence Log normal shadowing Testbed measurements

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IEEE 11th Conference on Industrial Electronics and Applications (ICIEA)

作者： Li, Baoping Commun Univ China Key Lab Media Audio & Video Minist Educ Beijing Peoples R China Henan Polytech Univ Jiaozuo Peoples R China

ISBN: (纸本)9781467386449

Cost initialization is an important step in both local and global stereo matching algorithms. Different similarity measures may perform differently in a particular location depending on the image structure. Different from the traditional similarity fusion strategies, we present a new fusion strategy which fuses similarity measures adaptively based on their performance on different image regions. The experimental results demonstrate that the proposed adaptive similarity fusion algorithm used in both local and global stereo matching algorithms is capable of providing high-quality disparity maps comparable to other fusion strategies.

关键词： Stereo Matching Adaptive Similarity Fusion local algorithm Global algorithm

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