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Genetic and Evolutionary Computation Conference (GECCO)

作者： Akimoto, Youhei Auger, Anne Hansen, Nikolaus Shinshu Univ Nagano Japan Inria Res Ctr Saclay Le Chesnay France

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Distributed self-tuning of sensor networks

Distributed self-tuning of sensor networks

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2nd Workshop on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks

作者： Karnik, Aditya Kumar, Anurag Borkar, Vivek Univ Waterloo Dept Elect & Comp Engn Waterloo ON N2L 3G1 Canada Indian Inst Sci Dept Elect Commun Engn Bangalore 560012 Karnataka India Tata Inst Fundamental Res Sch Technol & Comp Sci Bombay 400005 Maharashtra India

This work is motivated by the need for an ad hoc sensor network to autonomously optimise its performance for given task objectives and constraints. Arguing that communication is the main bottleneck for distributed computation in a sensor network we formulate two approaches for optimisation of computing rates. The first is a team problem for maximising the minimum communication throughput of sensors and the second is a game problem in which cost for each sensor is a measure of its communication time with its neighbours. We investigate adaptive algorithms using which sensors can tune to the optimal channel attempt rates in a distributed fashion. For the team problem, the adaptive scheme is a stochastic gradient algorithm derived from the augmented Lagrangian formulation of the optimisation problem. The game formulation not only leads to an explicit characterisation of the Nash equilibrium but also to a simple iterative scheme by which sensors can learn the equilibrium attempt probabilities using only the estimates of transmission and reception times from their local measurements. Our approach is promising and should be seen as a step towards developing optimally self-organising architectures for sensor networks.

关键词： sensor networks maxmin optimization games stochastic algorithms

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Comparative study of evolution strategies combined with approximation techniques for practical electromagnetic optimization problems

Comparative study of evolution strategies combined with appr...

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9th Biennial IEEE Conference on Electromagnetic Field Computation (CEFC)

作者： Farina, M Sykulski, JK Univ Pavia I-27100 Pavia Italy Univ Southampton Dept Elect Engn Southampton SO9 5NH Hants England

The paper addresses the practical problem of reducing the number of necessary function calls involving time consuming finite-element solutions by combining various evolution techniques with approximation methods based on Response Surface Methodology. A new algorithm is proposed which offers significant improvement of performance while preserving the quality of the final result. Comparisons are made between the new algorithm and different standard strategies in terms of reliability, efficiency and cost.

关键词： computational electromagnetics evolution techniques optimization stochastic algorithms

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Dynamic tree-like structures in P2P-networks

Dynamic tree-like structures in P2P-networks

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12th International Conference on Analytical and stochastic Modelling Techniques and Application

作者： Unger, H Wulff, M Univ Rostock Dept Comp Sci D-18051 Rostock Germany

ISBN: (纸本)1842331167

The search in P2P systems is still a problem because of the dynamic nature of these systems and the lack of central catalogs. In order to improve the search in P2P systems, a sorted structure is created from the content of all nodes in the system. Different from other approaches, a tree like structure is built by tokens which ate constantly moving between the nodes and carrying all. structural information.

关键词： P2P search stochastic algorithms dynamic structures

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Statistical Metamorphic Testing of Neural Network Based Intrusion Detection Systems

Statistical Metamorphic Testing of Neural Network Based Intr...

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IEEE International Conference on Cyber Security and Resilience (IEEE CSR)

作者： Reitman, Faqeer Ur Izurieta, Clemente Montana State Univ Gianforte Sch Comp Bozeman MT 59717 USA Montana State Univ Gianforte Sch Comp Idaho Natl Labs Bozeman MT USA

ISBN: (纸本)9781665402859

Testing computationally complex neural network-based applications (i.e. network intrusion detection systems) is a challenging task due to the absence of a test oracle. Metamorphic testing is a method to potentially solve the oracle problem when the correctness of individual output is difficult to determine. However, due to the stochastic nature of these applications, multiple runs with the same input can produce slightly different results;thus rendering traditional metamorphic testing technique inadequate. To address this problem, this paper proposes a statistical metamorphic testing technique to test neural network based Network Intrusion Detection Systems (N-IDSs) in a non-deterministic environment. We also performed mutation analysis to show the effectiveness of the proposed approach. The results show that the proposed method has a strong defect detection capability and is able to kill 100% implementation bugs in two neural network-based N-IDSs, and 66.66% in a neural network-based cancer prediction system.

关键词： Metamorphic testing oracle problem statistical hypothesis testing intrusion detection system neural networks stochastic algorithms

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A sum-over-paths impulse-response moment-extraction algorithm for IC-interconnect networks: Verification, coupled RIC lines

A sum-over-paths impulse-response moment-extraction algorith...

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IEEE/ACM International Conference on Computer Aided Design (ICCAD 2003)

作者： Le Coz, YL Krishna, D Petranovic, DM Loh, WM Bendix, P Rensselaer Polytech Inst ECSE Dept Troy NY 12180 USA

ISBN: (纸本)1581137621

We have created a stochastic impulse-response (IR) moment-extraction algorithm for RC circuit networks. It employs a newly discovered Feynman Sum-over-Paths Postulate. Full parallelism has been preserved. Numerical verification results for coupled RC lines confirmed rapid convergence. We believe this algorithm may find useful application in massively coupled electrical systems, such as those encountered in high-end digital-IC interconnects.

关键词： Feynman sum over paths IC-Interconnect modeling impulse-response moment extraction RC circuit networks stochastic algorithms

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Ergodic properties of weak asymptotic pseudotrajectories for semiflows

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Journal of Dynamics and Differential Equations 2000年第3期12.0卷 579-598页

作者： Benaïm, Michel Schreiber, Sebastian J. Department of Mathematics Université de Cergy-Pontoise Site de Saint Martin 95302 Cergy-Pontoise 2 Avenue Adolphe Chauvin France Department of Mathematics Western Washington University Bellingham WA 98225 United States

It is known that various deterministic and stochastic processes such as asymptotically autonomous differential equations or stochastic approximation processes can be analyzed by relating them to an appropriately chosen semiflow. Here, we introduce the notion of a stochastic process X being a weak asymptotic pseudotrajectory for a semiflow φ and are interested in the limiting behavior of the empirical measures of X. The main results are as follows: (1) the weak* limit points of the empirical measures for X axe almost surely φ-invariant measures;(2) given any semiflow φ, there exists a weak asymptotic pseudotrajectory X of φ such that the set of weak* limit points of its empirical measures almost surely equal the set of all ergodic measures for φ;and (3) if X is an asymptotic pseudotrajectory for a semiflow φ, then conditions on φ that ensure convergence of the empirical measures are derived. © 2000 Plenum Publishing Corporation.

关键词： Asymptotic autonomous semiflows Invariant measures Minimal center of attraction stochastic algorithms stochastic ordinary differential equation

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Widening the scope of an eigenvector stochastic approximation process and application to streaming PCA and related methods

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JOURNAL OF MULTIVARIATE ANALYSIS 2021年 182卷 104694-104694页

作者： Monnez, Jean-Marie Skiredj, Abderrahman Univ Lorraine CNRS Inria IECL F-54000 Nancy France CHRU Nancy INSERM CIC P F-54000 Nancy France Univ Lorraine CNRS IECL F-54000 Nancy France Ecole Natl Super Mines F-54000 Nancy France Inst Elie Cartan Lorraine BP 239 F-54506 Vandoeuvre Les Nancy France Ctr Invest Clin Plurithemat Nancy France Campus Artem CS 1423492 Rue Sergent Blandan F-54042 Nancy France

We prove the almost sure convergence of Oja-type processes to eigenvectors of the expectation B of a random matrix while relaxing the i.i.d. assumption on the observed random matrices (B-n) and assuming either (B-n) converges to B or (E[B-n vertical bar T-n]) converges to B where T-n is the sigma-field generated by the events before time n. As an application of this generalization, the online PCA of a random vector Z can be performed when there is a data stream of *** of Z, even when both the metric M used and the expectation of Z are unknown and estimated online. Moreover, in order to update the stochastic approximation process at each step, we are no longer bound to using only a mini-batch of observations of Z, but all previous observations up to the current step can be used without having to store them. This is useful not only when dealing with streaming data but also with Big Data as one can process the latter sequentially as a data stream. In addition the general framework of this process, unlike other algorithms in the literature, also covers the case of factorial methods related to PCA. (C) 2020 Elsevier Inc. All rights reserved.

关键词： Big data Data stream Eigenvectors Online estimation Principal component analysis stochastic algorithms stochastic approximation

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Greedy algorithms for Steiner Forest 15

Greedy Algorithms for Steiner Forest

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47th Annual ACM Symposium on Theory of Computing (STOC) held as part of the Federated Computing Research Conference

作者： Gupta, Anupam Kumar, Amit Carnegie Mellon Univ Pittsburgh PA 15213 USA IIT Delhi New Delhi India

ISBN: (纸本)9781450335362

In the Steiner Forest problem, we are given terminal pairs {s(i), t(i)}, and need to find the cheapest subgraph which connects each of the terminal pairs together. In 1991, Agrawal, Klein, and Ravi gave a primal-dual constant-factor approximation algorithm for this problem. Until this work, the only constant-factor approximations we know are via linear programming relaxations. In this paper, we consider the following greedy algorithm: Given terminal pairs in a metric space, a terminal is active if its distance to its partner is non-zero. Pick the two closest active terminals (say s(i), t(j), set the distance between them to zero, and buy a path connecting them. Recompute the metric, and repeat. It has long been open to analyze this greedy algorithm. Our main result shows that this algorithm is a constant-factor approximation. We use this algorithm to give new, simpler constructions of cost-sharing schemes for Steiner forest. In particular, the first "strict" cost-shares for this problem implies a very simple combinatorial sampling-based algorithm for stochastic Steiner forest.

关键词： approximation algorithms steiner forest greedy cost sharing stochastic algorithms

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On performance bounds for an affine combination of two LMS adaptive filters

On performance bounds for an affine combination of two LMS a...

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33rd IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Bershad, N. J. Bermudez, J. C. M. Tourneret, J. -Y Univ Calif Irvine 1621 Santiago Dr Newport Beach CA 92660 USA Univ Fed Santa Catarina Florianopolis SC Brazil IRIT ENSEEIHT TeSA F-31071 Toulouse France

ISBN: (纸本)9781424414833

This paper studies the statistical behavior of an affine combination of the outputs of two LMS adaptive filters that simultaneously adapt using the same white Gaussian input. The purpose of the combination is to obtain an LMS adaptive filter with fast convergence and small steady-state mean-square error (MSE). The linear combination studied is a generalization of the convex combination, in which the combination factor is restricted to the interval (0, 1). The viewpoint is taken that each of the two filters produces dependent estimates of the unknown channel. Thus, there exists a sequence of optimal affine combining coefficients which minimizes the MSE. The optimal unrealizable affine combiner is studied and provides the best possible performance for this class. Then, a new scheme is proposed for practical applications. It is shown that the practical scheme yields close-to-optimal performance when properly designed (as suggested by the theoretical optimal).

关键词： adaptive filters affine combination convex combination LMS algorithm stochastic algorithms

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