Noisy data
Gaussian mixture learning from noisy data
... We address the problem of learning a Gaussian mixture from a set of noisy data points. Each input point has an associated covariance matrix that can be inter- preted as the uncertainty by which this point ...
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Detection, reconstruction, and characterization algorithms from noisy data in multistatic wave imaging
... The main applications that we have in mind are medical imaging (such as mi- crowave and electrical impedance breast cancer detections), airport security screen- ing, geophysical exploration, and non-destructive testing; ...
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A NOVEL BIO-INSPIRED STATIC IMAGE COMPRESSION SCHEME FOR NOISY DATA TRANSMISSION OVER LOW-BANDWIDTH CHANNELS
... per right: coded/decoded image using the new codec. Lower left: coded/decoded image using JPEG. Lower right: coded/decoded im- age using JPEG2000. The performance of this coding scheme was tested against well established ...
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Online learning of acyclic conditional preference networks from noisy data
... Learning CP-nets, even by adding acyclicity constraints, is an NP-Complete problem [4]. Some works try to solve this problem by considering consistent preferences 1 , e.g. regression-based learning [8], [9], [14], ...
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Query-based learning of acyclic conditional preference networks from noisy data
... from noisy data Fabien Labernia and Florian Yger and Brice Mayag and Jamal Atif 1 ...in noisy data by search- ing in a principled way the variables that condition the other ...
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Nonparametric goodness-of fit testing in quantum homodyne tomography with noisy data
... of data has been considered in the framework of ideal detection [13, 12, 20, 3] as well as in the more general case of an efficiency parameter η belonging to the interval ]1/2, 1] ...
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PBDW method for state estimation: error analysis for noisy data and nonlinear formulation
... the set of measurement data. Several authors have proposed to exploit Bayesian approaches [14, 23, 9] that consist in adding certain prior assumptions and then searching through the most plausible solution through ...
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Behaviour Recognition on Noisy Data-streams Constrained by Complex Prior Knowledge
... 159 Conclusion I n this thesis, we explored different solutions to perform CEP under uncer- tainty. More precisely, we focused on the evaluation of a CE on a data- stream when it might be erroneous. In ...
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Nonparametric drift estimation for diffusions from noisy data
... L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignemen[r] ...
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Plant identification based on noisy web data: the amazing performance of deep learning (LifeCLEF 2017)
... from noisy data compared to trusted data (as usually done in supervised ...public data sources such as Wikimedia, iNaturalist, Flickr or various websites dedicated to ...aggregated data ...
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Adaptive Noisy Clustering
... 6 Conclusion This paper could be seen as a first step into the study of adaptive noisy clustering. Several problems remain open and could be the core of future works. Firstly, we obtain in Theorem 1 a non-adaptive ...
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Combining Bayesian inference and clustering for transport mode detection from sparse and noisy geolocation data
... mobility data is collected from smartphones, mining mobile network geolocation is non-trivial as it is a sparse, coarse and noisy data for which real transport labels are ...
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Anisotropic oracle inequalities in noisy quantization
... In the problem of risk minimization with noisy data, we provide oracle inequalities for an empirical risk minimization based on a deconvolution kernel. The risk of the deconvolution ERM mimics the risk of ...
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Joint coding-denoising optimization of noisy images
... I. I NTRODUCTION Images acquired by imaging systems are most of the time degraded by noise, which mainly comes from the imperfections of optical instruments. It is well-known that noise decreases the performances of ...
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Geometric Feature Estimators for Noisy Discrete Surfaces
... where − → n (Γ ν (p)) is the normal vector of the patch Γ ν (p). Other normal estimators have been proposed before. For instance, L. Pa- pier [4] estimates the normal vector at a point p of the surface using a weighted ...
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A Correlation-based Dissimilarity Measure for Noisy Patches
... As a last experiment, we investigate the usefulness of the quality measure in- troduced in Section 2.3, defined by Formula (6) with s = 15. Recall that this index relies on a local (patch-based) whiteness estimation, ...
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Noisy rumor spreading and plurality consensus
... handling noisy com- munication channels in the context of technological ...to noisy communica- tion channels, where every message transferred through a channel remains intact with small probability ...
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Noisy Broadcast Networks With Receiver Caching
... (XOR-ed) data during the delivery phase and simultaneously meet the demands of multiple ...the data rate that each receiver can locally retrieve from its ...
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Online learning with noisy side observations
... with noisy side observations fitting into our framework, where ac- tions correspond to alignments and the noisy side ob- servations give information about similar ...
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Equilibrium fluctuations in maximally noisy extended quantum systems
... Putting aside the quantum nature of the environments leads to consider model systems interacting with classical reservoirs or noisy external fields. In the context of quantum many body systems, and especially ...
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