Results 11 to 20 of about 187,956 (260)
A Kernel Method for Classification [PDF]
, 2004 Kernel Maximum Likelihood Hebbian Learning Scale Invariant Maps is a novel technique developed to facilitate the clustering of complex data effectively and efficiently and that is characterised for converging remarkably quickly. The combination of Maximum Likelihood Hebbian Learning Scale Invariant Map and the Kernel Space provides a very smooth scale ...
MacDonald, Donald +4 more
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Instrumental variable regression via kernel maximum moment loss
Journal of Causal Inference, 2023 We investigate a simple objective for nonlinear instrumental variable (IV) regression based on a kernelized conditional moment restriction known as a maximum moment restriction (MMR).
Zhang Rui +3 more
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Free-Breathing and Ungated Cardiac MRI Reconstruction Using a Deep Kernel Representation
Applied Sciences, 2023 Free-breathing and ungated cardiac MRI is a challenging problem due to the cardiac motion and respiration motion, which are not tracked. In this work, we propose an unsupervised deep kernel method for reconstructing real-time free-breathing and ungated ...
Qing Zou +3 more
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Information Theory With Kernel Methods
IEEE Transactions on Information Theory, 2023 We consider the analysis of probability distributions through their associated covariance operators from reproducing kernel Hilbert spaces. We show that the von Neumann entropy and relative entropy of these operators are intimately related to the usual notions of Shannon entropy and relative entropy, and share many of their properties.
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A More Efficient and Practical Modified Nyström Method
Mathematics, 2023 In this paper, we propose an efficient Nyström method with theoretical and empirical guarantees. In parallel computing environments and for sparse input kernel matrices, our algorithm can have computation efficiency comparable to the conventional Nyström
Wei Zhang +3 more
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Mathematics, 2022 For a fixed time, t, and a horizon time, b, the probability of default (PD) measures the probability that an obligor, that has paid his/her credit until time t, runs into arrears not later that time t+b.
Rebeca Peláez +2 more
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Invariance in Kernel Methods by Haar-Integration Kernels [PDF]
, 2005 We address the problem of incorporating transformation invariance in kernels for pattern analysis with kernel methods. We introduce a new class of kernels by so called Haar-integration over transformations. This results in kernel functions, which are positive definite, have adjustable invariance, can capture simultaneously various continuous or ...
Haasdonk, Bernard +2 more
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Functional Ergodic Time Series Analysis Using Expectile Regression
Mathematics, 2022 In this article, we study the problem of the recursive estimator of the expectile regression of a scalar variable Y given a random variable X that belongs in functional space.
Fatimah Alshahrani +5 more
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Attributed Relational SIFT-Based Regions Graph: Concepts and Applications
Machine Learning and Knowledge Extraction, 2020 In the real world, structured data are increasingly represented by graphs. In general, the applications concern the most varied fields, and the data need to be represented in terms of local and spatial connections.
Mario Manzo
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A novel approach to attention mechanism using kernel functions: Kerformer
Frontiers in Neurorobotics, 2023 Artificial Intelligence (AI) is driving advancements across various fields by simulating and enhancing human intelligence. In Natural Language Processing (NLP), transformer models like the Kerformer, a linear transformer based on a kernel approach, have ...
Yao Gan +3 more
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