[PDF] Top 20 Some effects in adaptive robust estimation under sparsity
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Some effects in adaptive robust estimation under sparsity
... of adaptive estimation when adaptation is considered with respect to the triplet "noise level – noise distribution – ...of estimation of the noise level can differ depending on whether the noise ... Voir le document complet
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Adaptive robust optimization with applications in inventory and revenue management
... decades in the field of dynamical systems and ...state estimation with a set-based membership description of the uncertainty, and the thesis Bertsekas [25] and paper Bertsekas and Rhodes [22] considered the ... Voir le document complet
213
Robust adaptive stabilization by delay under state parametric uncertainty and measurement bias
... obtained in [8], [9] for linear systems to adaptive stabilization of a class of nonlinear systems, which include a globally Lipschitz nonlinearity, unknown parameters, exogenous disturbances, and have a ... Voir le document complet
9
Adaptive robust estimation in sparse vector model
... estimators under sparsity when the noise level is unknown depends dramatically on the properties of the ...3. Estimation of the ` 2 -norm. In this section, we consider the problem of ... Voir le document complet
43
Adaptive robust estimation in sparse vector model
... estimators under sparsity when the noise level is unknown depends dramatically on the properties of the ...3. Estimation of the ℓ 2 -norm. In this section, we consider the problem of ... Voir le document complet
33
Adaptive GNSS Carrier Tracking Under Ionospheric Scintillation: Estimation vs. Mitigation
... synchronization, robust/adaptive tracking, GNSS, ionospheric scintillation, Kalman ...receivers in personal electronic devices and new scientific/industrial applications are pushing the limits of ... Voir le document complet
5
Optimal adaptive estimation of linear functionals under sparsity
... for some s ∈ {1, . . . , d}. Parameter s characterizes the sparsity of vector ...of estimation of L(θ) in this context arises, for example, if one wants to estimate the value of a function f ... Voir le document complet
18
Optimal adaptive estimation of linear functionals under sparsity
... for some s ∈ {1, . . . , d}. Parameter s characterizes the sparsity of vector ...of estimation of L(θ) in this context arises, for example, if one wants to estimate the value of a function f ... Voir le document complet
17
Robust conditional Weibull-type estimation
... regression estimation of conditional tails when the covariates are ...explored in extreme value theory compared to the fixed covariates, and only few papers can indeed be mentioned: Wang and Tsai (2009) ... Voir le document complet
36
Hyperspectral unmixing with spectral variability using adaptive bundles and double sparsity
... present in the scene, and their respective proportions (known as abundances) in each image pixel ...errors in abundance estimates ...variations in the acquisition process, the intensity of ... Voir le document complet
28
Some Effects of Evaporation in Binary Mixtures
... performed in the framework of the so-called “frozen- time” assumption, also called the quasi-steady state approximation (QSSA ...studies in the context of linear stability analyses (see for instance [29, ... Voir le document complet
221
Learning Heteroscedastic Models by Convex Programming under Group Sparsity
... group sparsity. Note that so far, inference under group-sparsity pioneered by ( Yuan and Lin , 2006 ; Lin and Zhang , 2006 ), has only focused on the simple case of known and constant noise level ... Voir le document complet
9
Advances in robust and adaptive optimization : algorithms, software, and insights
... as robust regret), and “relative robust” (which we refer to as competitive ...are, in general, less conservative than the absolute criterion, and that these criteria tend ...relative robust ... Voir le document complet
220
Adaptive Dantzig density estimation
... goals in this paper are mainly ...oracle in- equalities under very mild assumptions on the ...papers in the literature assume that the functions of the dictionary are bounded by a constant ... Voir le document complet
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Learning Heteroscedastic Models by Convex Programming under Group Sparsity
... applications in the afore- mentioned fields. In the present work, we propose a new method of estimation for model ( 1 ) that has the appealing properties of requiring neither homoscedas- ticity nor ... Voir le document complet
18
Robust Semiparametric DOA Estimation in non-Gaussian Environment
... adopted in array processing ...distributionally robust and semiparametric efficient R-estimator of the snapshot covariance matrix along with its exploitation to derive a MUSIC-based DOA estimation ... Voir le document complet
7
Robust Face Hallucination Using Quantization-Adaptive Dictionaries
... available in the image file to model the distortions afflicting the low-quality image b ...more robust to ...gain in performance especially at higher magnification ...the robust face ... Voir le document complet
6
Essays in robust estimation and inference in semi- and nonparametric econometrics
... data: in the first case, observations are dependent because of shocks that stem from a unique population while in the second case, shocks come from two distinct ...exchangeable in the polyadic case ... Voir le document complet
209
Non-negative Matrix Factorization under sparsity constraints to unmix in vivo spectrally resolved acquisitions
... introduce sparsity constraints. The constrained NMF algorithm was run on in vivo acquisitions, and successfully unmixed up to three differ- ent fluorescent ...with sparsity value imposed to specific ... Voir le document complet
5
Some effects of orchestra shells
... Some effects of orchestra shells Bradley, J. S. https://publications-cnrc.canada.ca/fra/droits L’accès à ce site Web et l’utilisation de son contenu sont assujettis aux conditions présentées dans le site ... Voir le document complet
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