Results 11 to 20 of about 48,655 (263)
Conditional Deep Gaussian Processes: Empirical Bayes Hyperdata Learning
Entropy, 2021 It is desirable to combine the expressive power of deep learning with Gaussian Process (GP) in one expressive Bayesian learning model. Deep kernel learning showed success as a deep network used for feature extraction.
Chi-Ken Lu, Patrick Shafto
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Conditional Deep Gaussian Processes: Multi-Fidelity Kernel Learning
Entropy, 2021 Deep Gaussian Processes (DGPs) were proposed as an expressive Bayesian model capable of a mathematically grounded estimation of uncertainty. The expressivity of DPGs results from not only the compositional character but the distribution propagation ...
Chi-Ken Lu, Patrick Shafto
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A moment-matching Ferguson & Klass algorithm [PDF]
Statistics and Computing, 2016 Completely random measures (CRM) represent the key building block of a wide variety of popular stochastic models and play a pivotal role in modern Bayesian Nonparametrics. A popular representation of CRMs as a random series with decreasing jumps is due to Ferguson and Klass (1972).
Julyan Arbel, Igor Prünster
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On the goodness-of-fits of the generalized lambda distribution on high-frequency stock index returns
Cogent Economics & Finance, 2022 In this paper, we investigate the goodness-of-fit of the flexible four-parameter generalized Lambda Distribution (GLD) for high-frequency 5-min returns sampled from the DJI30 Index.
Peterson Owusu Junior +2 more
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Identity Adaptation for Person Re-Identification
IEEE Access, 2018 Person re-identification (re-ID), which aims to identify the same individual from a gallery collected with different cameras, has attracted increasing attention in the multimedia retrieval community.
Qiuhong Ke +5 more
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CoRR, 2013 We give a new framework for proving the existence of low-degree, polynomial approximators for Boolean functions with respect to broad classes of non-product distributions. Our proofs use techniques related to the classical moment problem and deviate significantly from known Fourier-based methods, which require the underlying distribution to have some ...
Adam R. Klivans, Raghu Meka
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Entropy, 2017 In the Bayesian framework, the usual choice of prior in the prediction of homogeneous Poisson processes with random effects is the gamma one. Here, we propose the use of higher order maximum entropy priors.
Lotfi Khribi +2 more
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Reusing Preconditioners in Projection Based Model Order Reduction Algorithms
IEEE Access, 2020 Dynamical systems are pervasive in almost all engineering and scientific applications. Simulating such systems is computationally very intensive. Hence, Model Order Reduction (MOR) is used to reduce them to a lower dimension.
Navneet Pratap Singh, Kapil Ahuja
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A Line-Surface Integrated Algorithm for Underwater Terrain Matching [PDF]
Journal of Geodesy and Geoinformation Science, 2019 The current underwater terrain surface matching algorithm, which uses Hu moment as the similarity index, cannot gain accurate location due to the algorithm's disadvantage in detecting slight differences.
Lihua ZHANG,Xianpeng LIU,Shuaidong JIA,Yan SHI
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Parameterization of All Moment Matching Interpolants
2023 European Control Conference (ECC), 2023 We provide an enhancement of the notion of time-domain moments for systems of nonlinear differential-algebraic equations possessing feedforward terms. Following this, a parameterized family of systems achieving moment matching is given and, under mild conditions, it is shown that this family parameterizes all systems achieving moment matching and ...
Joel D. Simard +2 more
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