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Layered reasoning for randomized distributed algorithms

Mani Swaminathan, Joost-Pieter Katoen, Ernst-Rüdiger Olderog
2012 Formal Aspects of Computing  
This paper adopts the communication closed layer (CCL) concept of Elrad and Francez to the formal reasoning of randomized distributed algorithms.  ...  The feasibility of such layered separation is demonstrated on a randomized mutual exclusion algorithm by Kushilevitz and Rabin, complementing an algebraic approach (for analyzing this algorithm) by McIver  ...  We wish to thank Annabelle McIver for her feedback via email on the paper [MGCM08] . The comments from the reviewers helped in improving the presentation of our paper.  ... 
doi:10.1007/s00165-012-0231-x fatcat:ztjarcqotzhzxeokidd4umq26i

A modified ziggurat algorithm for generating exponentially- and normally-distributed pseudorandom numbers [article]

Christopher D McFarland
2014 arXiv   pre-print
Random values within these rectangular layers are then sampled by rejection.  ...  The algorithm divides a distribution into rectangular layers that stack on top of each other (resembling a Ziggurat), subsuming the desired distribution.  ...  Acknowledgments I would like to thank Nezar Abdennur, Anton Goloborodko, Maxim Imakaev, and Geoffrey Fudenberg for helpful discussions and comments.  ... 
arXiv:1403.6870v2 fatcat:6pwpwbhadraalikojz3wenqfqm

A Randomness Detection Method of ZigBee Protocol in a Wireless Sensor Network

Yongli Tang, Huanhuan Lian, Lixiang Li, Xiaojun Wang, Xixi Yan
2018 Sensors  
This study investigates the randomness detection of cryptographic algorithms in network security.  ...  Then this paper proposes a randomness detection method of ZigBee protocol in a wireless sensor network.  ...  Author Contributions: Y.T. and X.Y. performed conceptualization; X.Y. and H.L. performed algorithm design and result analysis; Y.T. and H.L wrote the manuscript; L.L. and X.W. revised and edited the manuscript  ... 
doi:10.3390/s18113962 fatcat:jj6e6rmleja3dmadgpdtazcc6q

Using Deep Neural Network Approximate Bayesian Network [article]

Jie Jia, Honggang Zhou, Yunchun Li
2018 arXiv   pre-print
The result shows that our model saturate as the number of training examples grow and we don't need many training examples to get reasonably good result.  ...  Compared with traditional approximate method likelihood weighting sampling algorithm, our method is much faster and gains higher accuracy in medium sized Bayesian Network.  ...  values for each random variable.  ... 
arXiv:1801.00282v2 fatcat:ppf6csgjwjhx3pajl6ak23zzw4

A copula-based visualization technique for a neural network [article]

Yusuke Kubo, Yuto Komori, Toyonobu Okuyama, Hiroshi Tokieda
2020 arXiv   pre-print
This algorithm suggests an approach for compressing a neural network and its parameter tuning because the algorithm identifies the paths that contribute to the classification or prediction results.  ...  In the proposed algorithm, the score estimated by the correlation coefficients between the neural network layers that can be calculated by applying the concept of a pair copula was defined.  ...  CVT can also use parameter tuning for the abovementioned reason.  ... 
arXiv:2003.12317v1 fatcat:u7gbjmv4z5ggzop3nc5yuvcp5m

Multi-attributed Graph Matching with Multi-layer Random Walks [chapter]

Han-Mu Park, Kuk-Jin Yoon
2016 Lecture Notes in Computer Science  
Then, we also propose a multiattributed graph matching algorithm based on the random walk centrality for the proposed multi-layer graph structure.  ...  proposed multi-layer graph structure and matching algorithm.  ...  For that reason, we empirically define a layer importance measure as the intersection of reweighted distribution and current assignment distribution.  ... 
doi:10.1007/978-3-319-46487-9_12 fatcat:6ymmjuhed5dq5caurmod2rbjca

The end-to-end rate control in multiple-hop wireless networks: Cross-layer formulation and optimal allocation

Chengnian Long, Bo Li, Qian Zhang, Bin Zhao, Bo Yang, Xinping Guan
2008 IEEE Journal on Selected Areas in Communications  
We then design a distributed algorithm that jointly considers random access and power control to adapt for the transport layer congestion status.  ...  complexity, how to design a distributed algorithm that can realize this formulation while maintaining the architectural modularity among different layers.  ...  The stochastic noisy feedback, however, is practically inevitable in the distributed algorithm implementation for the cross-layer design, especially for the wireless multi-hop networks with random access  ... 
doi:10.1109/jsac.2008.080513 fatcat:l6gs4bnt35fedjofsf2olzlrfy

Cloud Model Approach for Lateral Control of Intelligent Vehicle Systems

Hongbo Gao, Xinyu Zhang, Yuchao Liu, Deyi Li
2016 Scientific Programming  
This study focuses on designing an intelligent lateral control algorithm for vehicles at various speeds, formulating a strategy, introducing the Gauss cloud model and the cloud reasoning algorithm, and  ...  proposing a cloud control algorithm for calculating intelligent vehicle lateral offsets.  ...  GC distribution (GCD) is different from the GD because the GCD algorithm uses the Gauss random number twice, in which one random number is the basis of another random number.  ... 
doi:10.1155/2016/6842891 fatcat:ar6smvlfu5h7bpqxwa2n2khenq

Consistent Multiple Graph Matching with Multi-layer Random Walks Synchronization [article]

Han-Mu Park, Kuk-Jin Yoon
2018 arXiv   pre-print
Second, we propose a robust multiple graph matching method based on the multi-layer random walks framework.  ...  In our extensive experiments, the proposed method exhibits robust and accurate performance over the state-of-the-art multiple graph matching algorithms.  ...  4: repeat 5: for l, m = 1 to NG 6: (Calculate the next distribution) 7:t lm ← t lm P lm 8: for α = 1 to NL 9: (Reweighting random walks for each layer) 10: u α lm ← exp(ρ ·t α lm / max(t α lm )) 11: Bistochastic  ... 
arXiv:1712.02575v2 fatcat:jg366haufvah5kznupsx6sr6nq

Discretization from data streams

João Gama, Carlos Pinto
2006 Proceedings of the 2006 ACM symposium on Applied computing - SAC '06  
The proposed architecture process streaming examples in a single scan, in constant time and space even for infinite sequences of examples.  ...  Based on the statistics stored by the first layer, a second layer creates the final discretization.  ...  Acknowledgments Thanks to the financial support given by the FEDER, the Plurianual support attributed to LIACC, project ALES II (POSI/EIA/55340/2004), and Mario Alves for revising a previous version of  ... 
doi:10.1145/1141277.1141429 dblp:conf/sac/GamaP06 fatcat:6s5sjkp2gngw3ebcrhktfmkufu

Real-time Activity Recognition using Smartphone Accelerometer

Shuang Na, Kandethody M. Ramachandran, Ming Ji, Yicheng Tu
2019 Zenodo  
Then, we introduce two layer random forest classification for real time activity recognition on the smartphone by embedded accelerometers.  ...  To identify the real time activities, an online algorithm need be considered.  ...  reasoning of choosing random forest, we compared the results of training by KNN, and SVM, Boosting with Random forest in Fig5.  ... 
doi:10.5281/zenodo.3605956 fatcat:kbcautzy2be4plqppj2kifl3zi

On tuning deep learning models: a data mining perspective [article]

M.M. Ozturk
2020 arXiv   pre-print
In this paper, a tuning guideline is provided for researchers who cope with issues originated from hyperparameters of deep learning models.  ...  Even though high sparsity results in low accuracy, a uniform distribution is much more crucial to reach reliable results in terms of data mining.  ...  Acknowledgements We thank TUBITAK ULAKBIM, High Performance and Grid Computing Center (TRUBA Resources) for the numerical calculations reported in this work.  ... 
arXiv:2011.09857v1 fatcat:axh5fio2kjdxzghf452qg4l7bu

Near-Optimal Scheduling of Distributed Algorithms

Mohsen Ghaffari
2015 Proceedings of the 2015 ACM Symposium on Principles of Distributed Computing - PODC '15  
Suppose that we want to run distributed algorithms A 1 , A 2 . . . , A k in the CONGEST model, each taking at most dilation rounds, and where for each network edge, at most congestion messages need to  ...  This paper studies the question of how to run many distributed algorithms, solving independent problems, together as fast as possible.  ...  Acknowledgment The author thanks Nancy Lynch and Fabian Kuhn for valuable conversations about the conceptual point of the paper, i.e., studying the question of running many distributed algorithms together  ... 
doi:10.1145/2767386.2767417 dblp:conf/podc/Ghaffari15 fatcat:ybl5cyo5afh53ih4eibnone3jy

Longitudinal Control for Mengshi Autonomous Vehicle via Gauss Cloud Model

Hongbo Gao, Xinyu Zhang, Yuchao Liu, Deyi Li
2017 Sustainability  
Li et al. proposes a distributed H ∞ control method for the distribution of multi-car units [25]. The third way: the longitudinal control algorithm based on artificial intelligence algorithm. A.  ...  In our paper, we present a longitudinal control algorithm based on cloud model for Mengshi autonomous vehicle to ensure the dynamic stability and tracking performance of Mengshi autonomous vehicle.  ...  and analyzed the experiment results; Deyi Li evaluated and verified the algorithm, reviewed and commented on the paper; and Hongbo Gao and Xinyu Zhang wrote the paper.  ... 
doi:10.3390/su9122259 fatcat:ez25i2stsjd5be6ks2gy7gvs24

Generative Adversarial Networks in Estimation of Distribution Algorithms for Combinatorial Optimization [article]

Malte Probst
2016 arXiv   pre-print
Estimation of Distribution Algorithms (EDAs) require flexible probability models that can be efficiently learned and sampled.  ...  A key reason seems to be the large amount of noise present in the first EDA generations.  ...  Introduction Estimation of Distribution Algorithms (EDA) [7, 6] are metaheuristics for combinatorial and continuous non-linear optimization.  ... 
arXiv:1509.09235v2 fatcat:yhneqaql7jg2lfuobemcif5uzy
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