Results 51 to 60 of about 33,561,195 (290)
Synthesis of neural networks for spatio-temporal spike pattern recognition and processing
Frontiers in Neuroscience, 2013 The advent of large scale neural computational platforms has highlighted the lack of algorithms for synthesis of neural structures to perform predefined cognitive tasks.
Jonathan C Tapson +6 more
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Ain Shams Engineering Journal, 2017 In this article, we introduce a novel numerical scheme, the iterative reproducing kernel method (IRKM), for providing numerical approximate solutions of a certain class of time-fractional boundary value problem within favorable aspects of the reproducing
M. Al‐Smadi
semanticscholar +1 more source
Random Forests and Kernel Methods [PDF]
IEEE Transactions on Information Theory, 2016 Random forests are ensemble methods which grow trees as base learners and combine their predictions by averaging. Random forests are known for their good practical performance, particularly in high dimensional set-tings. On the theoretical side, several studies highlight the potentially fruitful connection between random forests and kernel methods.
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, 2003 Bayesian methods allow for a simple and intuitive representation of the function spaces used by kernel methods. This chapter describes the basic principles of Gaussian Processes, their implementation and their connection to other kernel-based Bayesian estimation methods, such as the Relevance Vector Machine.
Alexander J. Smola, Bernhard Schölkopf
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Applied SciencesMultivariate time series (MTS) clustering has been an essential research topic in various domains over the past decades. However, inherent properties of MTS data—namely, temporal dynamics and inter-variable correlations—make MTS clustering challenging ...
Sebin Heo +3 more
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A distance-based kernel for classification via Support Vector Machines
Frontiers in Artificial IntelligenceSupport Vector Machines (SVMs) are a type of supervised machine learning algorithm widely used for classification tasks. In contrast to traditional methods that split the data into separate training and testing sets, here we propose an innovative ...
Nazhir Amaya-Tejera +3 more
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Distributed Kernel Extreme Learning Machines for Aircraft Engine Failure Diagnostics
Applied Sciences, 2019 Kernel extreme learning machine (KELM) has been widely studied in the field of aircraft engine fault diagnostics due to its easy implementation. However, because its computational complexity is proportional to the training sample size, its application in
Junjie Lu, Jinquan Huang, Feng Lu
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Enumeration of convex polyominoes using the ECO method [PDF]
Discrete Mathematics & Theoretical Computer Science, 2003 ECO is a method for the enumeration of classes of combinatorial objects based on recursive constructions of such classes. In the first part of this paper we present a construction for the class of convex polyominoes based on the ECO method.
A. Del Lungo +3 more
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Analytic Combinatorics of Lattice Paths: Enumeration and Asymptotics for the Area [PDF]
Discrete Mathematics & Theoretical Computer Science, 2006 This paper tackles the enumeration and asymptotics of the area below directed lattice paths (walks on $\mathbb{N}$ with a finite set of jumps). It is a nice surprise (obtained via the "kernel method'') that the generating functions of the moments of the ...
Cyril Banderier, Bernhard Gittenberger
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Molecular Oncology, EarlyView.Many patients with urothelial cancer do not benefit from treatment with pembrolizumab, while at risk of severe side effects. Changes in the levels of circulating tumor DNA early during treatment, measured by a simple and affordable assay that can be easily implemented in the clinic, can be used as a prognostic tool to identify these patients.
Youssra Salhi +14 more
wiley +1 more source