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Annual ACM-Society for Industrial and Applied Mathmatics Symposium on Discrete algorithms

作者： Timothy M. Chan Ryan Williams Cheriton School of Computer Science University of Waterloo Computer Science Department Stanford University

ISBN: (纸本)9781510819672

We show how to solve all-pairs shortest paths on n nodes in deterministic n~3/2~(Ω({the square root of}(log n))) time, and how to count the pairs of orthogonal vectors among n 0-1 vectors in d = c log n dimensions in deterministic n~(2-1/O(log c)) time. These running times essentially match the best known randomized algorithms of (Williams, STOC'14) and (Abboud, Williams, and Yu, SODA 2015) respectively, and the ability to count was open even for randomized algorithms. By reductions, these two results yield faster deterministic algorithms for many other problems. Our techniques can also be used to deterministically count k-SAT assignments on n variable formulas in 2~(n-n/O(k)) time, roughly matching the best known running times for detecting satisfiability and resolving an open problem of Santhanam (2013). A key to our constructions is an efficient way to deterministically simulate certain probabilistic polynomials critical to the algorithms of prior work, carefully applying small-biased sets and modulus-amplifying polynomials.

关键词： orthogonal vector randomized algorithms deterministic shortest path Polynomial

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Iterative randomized robust linear regression 40

Iterative randomized robust linear regression

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40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015

作者： Kopsinis, Yannis Chouvardas, Symeon Theodoridis, Sergios University of Athens Dept. of Informatics and Telecommunications Athens Greece Computer Technology Institute and Press University Campus N. Kazantzaki Str Rio Greece

ISBN: (纸本)9781467369978

A promising approach when dealing with massive data sets is to apply randomized dimensionality reduction and then operate in lower dimensions. This paper deals with the randomized linear regression task in the case where the available data are sporadically corrupted. Instead of relying to minimization of norms, which are robust to outliers, an alternative route is taken. Building upon the observation that outliers can be detected, while operating in a low dimensional randomized projections produced embedding, a mechanism for iteratively detecting and excluding corrupted data is proposed. As a result, the linear regression is performed using conventional LS approximation, without the need to resort to linear programming-based 1norm minimization tasks. © 2015 IEEE.

关键词： randomized algorithms Robust Regression

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Simultaneous Perturbation Stochastic Approximation in Decentralized Load Balancing Problem

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IFAC-PapersOnLine 2015年第11 11期48卷 936-941页

作者： Amelina, Natalia Erofeeva, Victoria Granichin, Oleg Malkovskii, Nikolai St. Petersburg Russia Institute of Problems in Mechanical Engineering Russian Academy of Sciences ITMO University St. Petersburg Russia

In this work the load balancing problem is studied for decentralized stochastic network with unknown but bounded noise in measurements and varying productivities of agents. The load balancing problem is formulated as a consensus problem in a stochastic network. Consideration of Laplasian potential function corresponded to the network graph allows to introduce a new randomized local voting protocol with constant step-size which is based on simultaneous perturbation stochastic approximation algorithm. The conditions are formulated for the approximate consensus achievement which corresponds to achieving of a suboptimal level of agents' load. The new algorithm is illustrated by simulations. © 2015

关键词： Stochastic systems Approximation algorithms Approximation theory Multi agent systems Optimization Consensus problems Load balancing problem randomized algorithms Simultaneous perturbation stochastic approximation Simultaneous perturbation stochastic approximation algorithms Stochastic networks Unknown but bounded noise Varying productivity

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randomized Stochastic Approximation algorithms 13

Randomized Stochastic Approximation Algorithms

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13th European Control Conference (ECC)

作者： Amelin, Konstantin Granichin, Oleg Granichina, Olga St Petersburg State Univ Dept Math & Mech St Petersburg 198504 Russia Russian Acad Sci Inst Problems Mech Engn Moscow 117901 Russia Herzen State Pedag Univ Russia St Petersburg Russia

ISBN: (纸本)9783952426913

Multidimensional stochastic optimization plays an important role in analysis and control of many technical systems. To solve the challenging problems of multidimensional optimization, it was suggested to use the randomized algorithms of stochastic approximation with perturbed input which have simple forms and provide consistent estimates of the unknown parameters for observations under "almost arbitrary" noise. They are easily "incorporated" in the design of quantum devices to estimate gradient vector of a multi-variable function.

关键词： Approximation algorithms Approximation methods Computers Convergence Noise Quantum computing Vectors Approximation algorithms Approximation method quantum computing Computers Noise stochastic approximation Converge Quantum devices Gradient vector randomized algorithms Unknown parameter Cloning Vectors

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To Rent or to Buy in the Presence of Statistical Information: The Constrained Ski-Rental Problem

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IEEE-ACM TRANSACTIONS ON NETWORKING 2015年第4期23卷 1067-1077页

作者： Khanafer, Ali Kodialam, Murali Puttaswamy, Krishna P. N. Alcatel Lucent Bell Labs Holmdel NJ 07733 USA LinkedIn Corp Mountain View CA 94043 USA

Cloud service providers enable tenants to elastically scale resources to meet their demands. While running cloud applications, a tenant aiming to minimize cost is often challenged with crucial tradeoffs. For instance, upon each arrival of a query, a Web application can either choose to pay for CPU to compute the response fresh, or pay for cache storage to store the response to reduce future compute costs. The Ski-Rental problem abstracts such scenarios where a tenant is faced with a to-rent-or-to-buy tradeoff;in its basic form, a skier should choose between renting or buying a set of skis without knowing the number of days she will be skiing. In the multislope version of the Ski-Rental problem, the skier can choose among multiple services that differ in their buying and renting prices. In this paper, we introduce a variant of the classical Ski-Rental problem in which we assume that the skier knows the first (or second) moment of the distribution of the number of ski days in a season. We also extend the classical multislope Ski-Rental problem, where the skier can choose among multiple services, to this setting. We demonstrate that utilizing this information leads to achieving the best worst-case expected competitive ratio performance. Our method yields a new class of randomized algorithms that provide arrivals-distribution-free performance guarantees. Simulations illustrate that our scheme exhibits robust average-cost performance that combines the best of the well-known deterministic and randomized schemes previously proposed to tackle the Ski-Rental problem.

关键词： Cloud cost optimization game theory randomized algorithms ski-rental problem

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Local Voting Protocol for Differentiated Consensuses in a Stochastic Network with Priorities

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IFAC-PapersOnLine 2015年第11 11期48卷 954-959页

作者： Amelina, N. Granichin, O. Granichina, O. Ivanskiy, Y. Jiang, Y. Russia Institute of Problems in Mechanical Engineering Russian Academy of Sciences ITMO University Russia and Herzen State Pedagogical University St. Petersburg Russia Trondheim Norway

In this paper a distributed stochastic network system with incoming tasks that are classified with priorities is studied. The network system is assumed to have variable topology, and agents are not necessarily always connected to each other. In addition, the observations about neighbors' states are supposed to be obtained with random noise and delays. To ensure eficient operation of this network system, a novel control strategy is proposed. With this strategy, network resources are allocated in a randomized way with probabilities corresponding to each priority class. To maintain the balanced load across the network for different priorities, a socalled “Differentiated consensuses” problem is examined. This consensus problem is that, in a system with multiple classes, consensus is targeted for each class, which may be different among classes. In this paper, the ability of the proposed control protocol to maintain almost balanced load, i.e. approximate consensus for every priority class across the network, is proved. In addition, a numerical example that illustrates the proposed control strategy and the results of simulations are provided. © 2015

关键词： Internet protocols Multi agent systems Stochastic control systems Stochastic systems consensus achievement Consensus problems Control protocols Control strategies Multiagent networks randomized algorithms Stochastic networks Variable topologies

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Online Nonlinear Classification for High-Dimensional Data 4

Online Nonlinear Classification for High-Dimensional Data

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IEEE International Congress on Big Data

作者： Vanli, N. Denizcan Ozkan, Huseyin Delibalta, Ibrahim Kozat, Suleyman S. Bilkent Univ Dept Elect & Elect Engn Ankara Turkey AVEA Commun Serv Inc AveaLabs Istanbul Turkey Koc Univ Grad Sch Social Sci & Humanities Istanbul Turkey

ISBN: (纸本)9781467372787

We study online binary classification problem under the empirical zero-one loss function. We introduce a novel randomized classification algorithm based on highly dynamic hierarchical models that partition the feature space. Our approach jointly and sequentially learns the partitioning of the feature space, the optimal classifier among all doubly exponential number of classifiers defined by the tree, and the individual region classifiers in order to directly minimize the cumulative loss. Although we adapt the entire hierarchical model to minimize a global loss function, the computational complexity of the introduced algorithm scales linearly with the dimensionality of the feature space and the depth of the tree. Furthermore, our algorithm can be applied to any streaming data without requiring a training phase or prior information, hence processes data on-the-fly and then discards it, which makes the introduced algorithm significantly appealing for applications involving "big data". We evaluate the performance of the introduced algorithm over different real data sets.

关键词： Online classification randomized algorithms nonlinear classification high-dimensional data

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randomized algorithms and their application to renewable energy systems

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IFAC Proceedings Volumes 2010年第1期43卷 163-168页

作者： A. Luque T. Alamo Departamento de Ingenieria de Sistemas y Automatica. Escuela Superior de Ingenieros de Sevilla. Camino de los Descubrimientos s.n. 41092 Sevilla

In this paper we show how randomized algorithms can be applied to the design of a robust controller. The design objective consists on the problem of finding a controller such that guarantees a proper behavior in front of uncertainties, taking into account the worst possible situation (robust solution). A randomized algorithm that provides a probabilistic solution is proposed. The proposed strategy is applied to the control of the hot water production system installed at the University Hospital “Virgen del Rocio” (Seville, Spain).

关键词： randomized algorithms uncertain system sample size

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Using Random Butterfly Transformations in Parallel Schur Complement-Based Preconditioning

Using Random Butterfly Transformations in Parallel Schur Com...

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3rd International Conference on Innovative Network Systems and Applications (iNetSApp) held in conjunction with Federated Conference on Computer Science and Information Systems (FedCSIS)

作者： Baboulin, Marc Jamal, Aygul Sosonkina, Masha Univ Paris 11 Bat 425 F-91405 Orsay France Old Dominion Univ Norfolk VA 23529 USA

ISBN: (纸本)9788360810668

We propose to use a randomization technique based on Random Butterfly Transformations (RBT) in the Algebraic Recursive Multilevel Solver (ARMS) to improve the preconditioning phase in the iterative solution of sparse linear systems. We integrated the RBT technique into the parallel version of ARMS (pARMS). The preliminary experimental results on some matrices from the Davis' collection show an improvement of the convergence and accuracy of the results when compared with existing implementations of the pARMS preconditioner.

关键词： iterative methods matrix algebra parallel algorithms randomised algorithms recursive estimation RBT technique algebraic recursive multilevel solver iterative solution matrices pARMS preconditioner parallel ARMS parallel Schur complement-based preconditioning preconditioning phase improvement random butterfly transformations randomization technique sparse linear systems Accuracy Iterative methods Linear systems Program processors Sparse matrices Symmetric matrices Yttrium iterative methods Linear system iterative solution Program processors Symmetric matrix recursive estimation Sparse matrix matrix algebra Parallel algorithms Rare earths yttrium matrices randomized algorithms

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Field Oriented Control for Permanent Magnet Synchronous Motor Based on DSP Experimental Platform 27

Field Oriented Control for Permanent Magnet Synchronous Moto...

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27th Chinese Control and Decision Conference (CCDC)

作者： Zhang, Xiangnan Xie, Xiaohua Yao, Rongzi Natl Automobile Dynam Simulat Lab Changchun 130025 Peoples R China Jilin Univ Dept Control Sci & Engn Changchun 130025 Peoples R China

ISBN: (纸本)9781479970162

Due to the strongly coupled and multivariable characteristics of the dynamic mathematical model of permanent magnet synchronous motor(PMSM), a strategy of held oriented control(FOC) for PMSM based on DSP experimental platform is presented to decouple the torque current and the flux current in this paper. Firstly, the mathematical model of PMSM is established according to its characteristics. Then, the PI controller of control system is designed in simulink and the parameters of the PI controller are selected through randomized algorithms. Finally, the off-line simulation in simulink and the semi-physical simulation research on DSP experimental platform are implemented. The experimental results verify and reflect the effectiveness of the control strategy.

关键词： PMSM Field Oriented Control randomized algorithms DSP PI Controller

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