Relevant bibliographies by topics / Wolff algorithm

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Academic literature on the topic 'Wolff algorithm'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Wolff algorithm"

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LIMA, F. W. S. "MIXED ALGORITHMS IN THE ISING MODEL ON DIRECTED BARABÁSI–ALBERT NETWORKS." International Journal of Modern Physics C 17, no. 06 (2006): 785–93. http://dx.doi.org/10.1142/s0129183106008753.

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On directed Barabási–Albert networks with two and seven neighbours selected by each added site, the Ising model does not seem to show a spontaneous magnetisation. Instead, the decay time for flipping of the magnetisation follows an Arrhenius law for Metropolis and Glauber algorithms, but for Wolff cluster flipping the magnetisation decays exponentially with time. On these networks the magnetisation behaviour of the Ising model, with Glauber, HeatBath, Metropolis, Wolf or Swendsen–Wang algorithm competing against Kawasaki dynamics, is studied by Monte Carlo simulations. We show that the model e
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BAE, S., S. H. KO, and P. D. CODDINGTON. "PARALLEL WOLFF CLUSTER ALGORITHMS." International Journal of Modern Physics C 06, no. 02 (1995): 197–210. http://dx.doi.org/10.1142/s0129183195000150.

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The Wolff single-cluster algorithm is the most efficient method known for Monte Carlo simulation of many spin models. Due to the irregular size, shape and position of the Wolff clusters, this method does not easily lend itself to efficient parallel implementation, so that simulations using this method have thus far been confined to workstations and vector machines. Here we present two parallel implementations of this algorithm, and show that one gives fairly good performance on a MIMD parallel computer.
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Campos, P. R. A., and R. N. Onody. "Critical Dynamics Behavior of the Wolff Algorithm in the Site-Bond-Correlated Ising Model." International Journal of Modern Physics C 09, no. 06 (1998): 861–65. http://dx.doi.org/10.1142/s0129183198000807.

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Here we apply the Wolff single-cluster algorithm to the site-bond-correlated Ising model and study its critical dynamical behavior. We have verified that the autocorrelation time diminishes in the presence of dilution and correlation, showing that the Wolff algorithm performs even better in such situations. The critical dynamical exponents are also estimated.
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TALAPOV, A. L., V. B. ANDREICHENKO, VI S. DOTSENKO, and L. N. SHCHUR. "FIRST CLUSTER ALGORITHM SPECIAL PURPOSE PROCESSOR." International Journal of Modern Physics C 04, no. 04 (1993): 787–804. http://dx.doi.org/10.1142/s0129183193000653.

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We describe the architecture of the special purpose processor built to realize in hardware cluster Wolff algorithm, which is not hampered by a critical slowing down. The processor simulates two-dimensional Ising-like spin systems. With minor changes the same very effective architecture, which can be defined as a Memory Machine, can be used to study phase transitions in a wide range of models in two or three dimensions.
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TALAPOV, A. L., L. N. SHCHUR, V. B. ANDREICHENKO, and VL S. DOTSENKO. "CLUSTER ALGORITHM SPECIAL PURPOSE PROCESSOR." Modern Physics Letters B 06, no. 18 (1992): 1111–19. http://dx.doi.org/10.1142/s0217984992001976.

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We describe a Special Purpose Processor, realizing the Wolff algorithm in hardware, which is fast enough to study the critical behaviour of 2D Ising-like systems containing more than one million spins. The processor has been checked to produce correct results for a pure Ising model and for Ising model with random bonds. Its data also agree with the Nishimori exact results for spin glass. Only minor changes of the SPP design are necessary to increase the dimensionality and to take into account more complex systems such as Potts models.
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Marrakchi, S., I. Kammoun, and S. Kachboura. "Wolff-Parkinson-White Syndrome Mimics a Conduction Disease." Case Reports in Medicine 2014 (2014): 1–5. http://dx.doi.org/10.1155/2014/789537.

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Background. It is important to recognise Wolff-Parkinson-White (WPW) syndrome in electrocardiograms (ECG), as it may mimic ischaemic heart disease, ventricular hypertrophy, and bundle branch block. Recognising WPW syndrome allows for risk stratification, the identification of associated conditions, and the institution of appropriate management.Objective. The present case showed that electrophysiological study is indicated in patients with abnormal ECG and syncope.Case Report. A 40-year-old man with Wolff-Parkinson-White syndrome was presented to emergency with syncope. A baseline ECG was a com
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Oishi-Tomiyasu, Ryoko. "Mathematical Tools that Connect Different Indexing Analyses." Proceedings 62, no. 1 (2020): 8. http://dx.doi.org/10.3390/proceedings2020062008.

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As mathematical tools that can be commonly used for indexing analyses from different types of experimental patterns, we have recently developed (i) rules on forbidden hkl’s that can be used even when the space group and setting are unknown, (ii) an algorithm for error-stable Bravais lattice determination, (iii) generalization of the de Wolff figure of merit for powder diffraction (1D data) to data in higher-dimensions such as Kikuchi patterns (2D data) by electron backscatter diffraction (EBSD). In particular, (ii) could be used in a variety of situations, not just for indexing. It is explaine
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MITROVIĆ, BOŽIDAR, and MICHELLE A. PRZEDBORSKI. "MONTE CARLO STUDY OF THE XY-MODEL ON SIERPIŃSKI CARPET." International Journal of Modern Physics C 25, no. 02 (2014): 1350087. http://dx.doi.org/10.1142/s0129183113500873.

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We have performed a Monte Carlo (MC) study of the classical XY-model on a Sierpiński carpet, which is a planar fractal structure with infinite order of ramification and fractal dimension 1.8928. We employed the Wolff cluster algorithm in our simulations and our results, in particular those for the susceptibility and the helicity modulus, indicate the absence of finite-temperature Berezinskii–Kosterlitz–Thouless (BKT) transition in this system.
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Djeddaï, C., C. Karsenty, A. Maltret, et al. "Wolff Parkinson White syndrome: Validation of an algorithm for identifying accessory pathway in children." Archives of Cardiovascular Diseases Supplements 13, no. 4 (2021): 284. http://dx.doi.org/10.1016/j.acvdsp.2021.06.025.

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Murtazaev, A. K., A. B. Babaev, and G. Y. Ataeva. "Critical properties of 2d disordered 3-state antiferromagnetic potts model ON TRIANGULAR LATTICE." EPJ Web of Conferences 185 (2018): 11001. http://dx.doi.org/10.1051/epjconf/201818511001.

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By introducing a small amount of non-magnetic impurities into an antiferromagnetic (AF) two-dimensional (2D) Potts model on a triangular lattice it is that the impurities in spin systems described by this model result in the change of a first order to a second-order phase transition. The systems with linear sizes L × L = N, L = 9-144 are considered. Investigations are performed using the standard Metropolis algorithm along with Monte-Carlo single-cluster Wolff algorithm. On the basis of the theory of finite-size scaling, critical exponents (CE) are calculated: the heat capacity α, the suscepti
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Dissertations / Theses on the topic "Wolff algorithm"

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Meier, Hannes. "Phase transitions in novel superfluids and systems with correlated disorder." Doctoral thesis, KTH, Statistisk fysik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-160929.

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Condensed matter systems undergoing phase transitions rarely allow exact solutions. The presence of disorder renders the situation  even worse but collective Monte Carlo methods and parallel algorithms allow numerical descriptions. This thesis considers classical phase transitions in disordered spin systems in general and in effective models of superfluids with disorder and novel interactions in particular. Quantum phase transitions are considered via a quantum to classical mapping. Central questions are if the presence of defects changes universal properties and what qualitative implications
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Cook, Philip R. "Limitations and Extensions of the WoLF-PHC Algorithm." Diss., CLICK HERE for online access, 2007. http://contentdm.lib.byu.edu/ETD/image/etd2109.pdf.

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Nöllenburg, Martin [Verfasser], and A. [Akademischer Betreuer] Wolff. "Network Visualization : Algorithms, Applications, and Complexity / Martin Nöllenburg. Betreuer: A. Wolff." Karlsruhe : KIT-Bibliothek, 2009. http://d-nb.info/1013762533/34.

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Rodrigues, Félix Carvalho. "Smoothed analysis in Nash equilibria and the Price of Anarchy." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2012. http://hdl.handle.net/10183/54866.

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São analisados nesta dissertação problemas em teoria dos jogos, com enfoque no efeito que perturbações acarretam em jogos. A análise suavizada (smoothed analysis) é utilizada para tal análise, e dois tipos de jogos são o foco principal desta dissertação, jogos bimatrizes e o problema de atribuição de tráfego (Traffic Assignment Problem.) O algoritmo de Lemke-Howson é um método utilizado amplamente para computar um equilíbrio Nash de jogos bimatrizes. Esse problema é PPAD-completo (Polynomial Parity Arguments on Directed graphs), e existem instâncias em que um tempo exponencial é necessário par
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Lakshminarayanan, Srivathsan. "Nature Inspired Grey Wolf Optimizer Algorithm for Minimizing Operating Cost in Green Smart Home." University of Toledo / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1438102173.

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Wolff, Pascal [Verfasser], Hans-Christian [Akademischer Betreuer] Pfohl, Jiazhen [Akademischer Betreuer] Huo, and Christoph [Akademischer Betreuer] Glock. "Resource Planning in Cross-Docking Platforms - Models and Algorithms / Pascal Wolff ; Hans-Christian Pfohl, Jiazhen Huo, Christoph Glock." Darmstadt : Universitäts- und Landesbibliothek, 2021. http://d-nb.info/1233429507/34.

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Campos, Paulo Roberto de Araujo. "Comportamento crítico dinâmico de algoritmo de Wolff no Modelo de Ising com correlação de sítios e ligações." Universidade de São Paulo, 1998. http://www.teses.usp.br/teses/disponiveis/76/76131/tde-10092008-092104/.

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Estudamos o comportamento dinâmico do algoritmo de Wolff no modelo de Ising diluído com correlação de sítios e ligações (modelo SBC). Nosso objetivo principal foi estudar a performance deste algoritmo em um sistema onde além da desordem à presença de impurezas não magnéticas, houvesse mais um parâmetro presente, a correlação espacial. Além disto foi possível obter o diagrama de fases para o modelo, o qual possibilita entendermos um pouco o efeito da desordem e da correlação no sistema.Verificamos que o diagrama de fases por nós obtidos está em boa concordância com os dados experimentais obtido
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Kwok, Hing-Wah Computer Science &amp Engineering Faculty of Engineering UNSW. "Hierarchical reinforcement learning in adversarial environments." Publisher:University of New South Wales. Computer Science & Engineering, 2009. http://handle.unsw.edu.au/1959.4/43424.

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It is known that one of the downfalls of reinforcement learning is the amount of time required to learn an optimal policy. This especially holds true for environments with large state spaces or environments with multiple agents. It is also known that standard Q-Learning develops a deterministic policy, and so in games where a stochastic policy is required (such as rock, paper, scissors) a Q-Learner opponent can be defeated without too much difficulty once the learning has ceased. Initially we investigated the impact that the MAXQ hierarchical reinforcement learning algorithm had in an adversa
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Bhandare, Ashray Sadashiv. "Bio-inspired Algorithms for Evolving the Architecture of Convolutional Neural Networks." University of Toledo / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1513273210921513.

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Budig, Benedikt [Verfasser], Dijk Thomas C. [Gutachter] van, Alexander [Gutachter] Wolff, and Yao-Yi [Gutachter] Chiang. "Extracting Spatial Information from Historical Maps: Algorithms and Interaction / Benedikt Budig ; Gutachter: Thomas C. van Dijk, Alexander Wolff, Yao-Yi Chiang." Würzburg : Würzburg University Press, 2018. http://d-nb.info/1174143495/34.

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Book chapters on the topic "Wolff algorithm"

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Ali, Ahmed F., and Mohamed A. Tawhid. "Grey Wolf Optimizer." In Swarm Intelligence Algorithms. CRC Press, 2020. http://dx.doi.org/10.1201/9780429422614-16.

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Badar, Altaf Q. H. "Grey Wolf Optimizer." In Evolutionary Optimization Algorithms. CRC Press, 2021. http://dx.doi.org/10.1201/9781003206477-8.

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Rezaei, Hossein, Omid Bozorg-Haddad, and Xuefeng Chu. "Grey Wolf Optimization (GWO) Algorithm." In Advanced Optimization by Nature-Inspired Algorithms. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-5221-7_9.

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Ali, Ahmed F., and Mohamed A. Tawhid. "Grey Wolf Optimizer - Modifications and Applications." In Swarm Intelligence Algorithms. CRC Press, 2020. http://dx.doi.org/10.1201/9780429422607-16.

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Meiwal, Priyanka, Harish Sharma, and Nirmala Sharma. "Neighbourhood-Inspired Grey Wolf Optimizer." In Algorithms for Intelligent Systems. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5077-5_11.

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Gamrath, Gerald, and Marco E. Lübbecke. "Experiments with a Generic Dantzig-Wolfe Decomposition for Integer Programs." In Experimental Algorithms. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13193-6_21.

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Meiwal, Priyanka, Harish Sharma, and Nirmala Sharma. "Fully Informed Grey Wolf Optimizer Algorithm." In Algorithms for Intelligent Systems. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-4936-6_55.

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Okwu, Modestus O., and Lagouge K. Tartibu. "Grey Wolf Optimizer." In Metaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-61111-8_5.

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Cristescu, Răzvan, Baltasar Beferull-Lozano, and Martin Vetterli. "Networked Slepian-Wolf: Theory and Algorithms." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24606-0_4.

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Sharma, Ankit Kumar, Akash Saxena, Dheeraj Kumar Palwalia, and Bhanu Pratap Soni. "An Optimal Demand Response Strategy Using Gray Wolf Optimization." In Algorithms for Intelligent Systems. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4604-8_72.

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Conference papers on the topic "Wolff algorithm"

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Gu, Bin, Wenhan Xian, and Heng Huang. "Asynchronous Stochastic Frank-Wolfe Algorithms for Non-Convex Optimization." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/104.

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Asynchronous parallel stochastic optimization for non-convex problems becomes more and more important in machine learning especially due to the popularity of deep learning. The Frank-Wolfe (a.k.a. conditional gradient) algorithms has regained much interest because of its projection-free property and the ability of handling structured constraints. However, our understanding of asynchronous stochastic Frank-Wolfe algorithms is extremely limited especially in the non-convex setting. To address this challenging problem, in this paper, we propose our asynchronous stochastic Frank-Wolfe algorithm (A
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Cheung, Edward, and Yuying Li. "Projection Free Rank-Drop Steps." In Twenty-Sixth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/213.

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The Frank-Wolfe (FW) algorithm has been widely used in solving nuclear norm constrained problems, since it does not require projections. However, FW often yields high rank intermediate iterates, which can be very expensive in time and space costs for large problems. To address this issue, we propose a rank-drop method for nuclear norm constrained problems. The goal is to generate descent steps that lead to rank decreases, maintaining low-rank solutions throughout the algorithm. Moreover, the optimization problems are constrained to ensure that the rank-drop step is also feasible and can be rea
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Tolstikhin, A., and I. Bychkov. "Swarm optimization approach to non-stationary physical eld survey problem using a group of autonomous underwater vehicles." In The International Workshop on Information, Computation, and Control Systems for Distributed Environments. Crossref, 2020. http://dx.doi.org/10.47350/iccs-de.2020.25.

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The paper considers the problem of searching for the source of a non-stationary physical eld. We assume that the use of swarm algorithms may be applicable in this case. A hybrid of the Whale Optimization Algorithm and Grey Wolf Optimizer is proposed in this paper. The algorithm has several advantages over its origins: a more precise solution of the optimization problem for low-dimensional functions and a higher convergence rate of the first iterations. Two modications were made to adapt the algorithm to the requirements of the problem. The proposed algorithm is used as a basis for a control st
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Zhao, Qiangyi, Ran Tao, Jiangning Li, and Yahui Mu. "An Improved Wolf Pack Algorithm." In 2020 Chinese Control And Decision Conference (CCDC). IEEE, 2020. http://dx.doi.org/10.1109/ccdc49329.2020.9164486.

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Zhu, Jianyun, Zhenhua Wei, and Taizhao Li. "Research of Wolf Pack Algorithm." In 2018 International Conference on Intelligent Transportation, Big Data & Smart City (ICITBS). IEEE, 2018. http://dx.doi.org/10.1109/icitbs.2018.00180.

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Chi, Mingwen. "An improved wolf pack algorithm." In the International Conference. ACM Press, 2019. http://dx.doi.org/10.1145/3371425.3371462.

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Song, Qun, Simon Fong, and Rui Tang. "Self-Adaptive Wolf Search Algorithm." In 2016 5th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI). IEEE, 2016. http://dx.doi.org/10.1109/iiai-aai.2016.102.

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Joshi, Susheel, and Jagdish Chand Bansal. "Grey wolf gravitational search algorithm." In 2016 International Workshop on Computational Intelligence (IWCI). IEEE, 2016. http://dx.doi.org/10.1109/iwci.2016.7860371.

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Gao, Hongchang, Hanzi Xu, and Slobodan Vucetic. "Sample Efficient Decentralized Stochastic Frank-Wolfe Methods for Continuous DR-Submodular Maximization." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/482.

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Continuous DR-submodular maximization is an important machine learning problem, which covers numerous popular applications. With the emergence of large-scale distributed data, developing efficient algorithms for the continuous DR-submodular maximization, such as the decentralized Frank-Wolfe method, became an important challenge. However, existing decentralized Frank-Wolfe methods for this kind of problem have the sample complexity of $\mathcal{O}(1/\epsilon^3)$, incurring a large computational overhead. In this paper, we propose two novel sample efficient decentralized Frank-Wolfe methods to
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Tang, Rui, Simon Fong, Xin-She Yang, and Suash Deb. "Wolf search algorithm with ephemeral memory." In 2012 Seventh International Conference on Digital Information Management (ICDIM). IEEE, 2012. http://dx.doi.org/10.1109/icdim.2012.6360147.

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