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Spatial Markov Kernels for Image Categorization and Annotation
IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 2011This paper presents a novel discriminative stochastic method for image categorization and annotation. We first divide the images into blocks on a regular grid and then generate visual keywords through quantizing the features of image blocks. The traditional Markov chain model is generalized to capture 2-D spatial dependence between visual keywords by ...
, Zhiwu Lu, H H S, Ip
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Aspects of large random Markov kernels
Stochastics, 2009We briefly review certain asymptotic properties of random Markov kernels on a finite state space. These models can be thought of as finite Markov chains in random environment. Here, the asymptotics are taken with respect to the cardinality of the state space. We study, for instance, the behaviour of the normalized invariant vector, the global behaviour
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High-order Markov kernels for intrusion detection
Neurocomputing, 2008In intrusion detection systems, sequences of system calls executed by running programs can be used as evidence to detect anomalies. Markov chain is often adopted as the model in the detection systems, in which high-order Markov chain model is well suited for the detection, but as the order of the chain increases, the number of parameters of the model ...
Chuanhuan Yin +2 more
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Apnea Detection Based on Hidden Markov Model Kernel
20110 ...
Travieso, Carlos M. +3 more
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Universal Markov Kernels for Quantum Observables
2019We prove the existence of a universal Markov kernel, i.e., a Markov kernel µ such that every commutative POVM F is the smearing of a selfadjoint operator AF with the smearing realized through µ. The relevance of the smearing is illustrated in connection with the problem of the joint measurability of two quantum observables.
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Continuous Affine Functions on the Space of Markov Kernels
Theory of Probability & Its Applications, 1986Reprint from Teor. Veroyatn. Primen. 30, No.3, 486-498 (1985; Zbl 0584.60005).
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Representations of state space transformations by Markov kernels
International Journal of Theoretical Physics, 1991zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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In situ learning using intrinsic memristor variability via Markov chain Monte Carlo sampling
Nature Electronics, 2021Thomas Dalgaty +2 more
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