[PDF] Top 20 Sparse Representation of Multivariate Extremes with Applications to Anomaly Ranking
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Sparse Representation of Multivariate Extremes with Applications to Anomaly Ranking
... Abstract Extremes play a special role in Anomaly Detec- ...used to design novel statistical learning methods for Anomaly ...EVT to learn how to rank observations in a high ... Voir le document complet
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A Multivariate Extreme Value Theory Approach to Anomaly Clustering and Visualization
... vised anomaly detection is now the subject of much attention in the data science literature, see ...coincide with rare measurements that are extremes, ...for anomaly detection are based ... Voir le document complet
26
Machine learning and extremes for anomaly detection
... 7. Sparse Representation of Multivariate Extremes 109 Also, new observations outside the ‘observed support’ are most often predicted as ...many applications (e.g. air- craft ... Voir le document complet
221
A multivariate extreme value theory approach to anomaly clustering and visualization
... representation of the extremal dependence structure is obtained when only a few such groups of variables can be exhibited (compared to 2 d − 1) and/or when these groups involve a small number ... Voir le document complet
26
Sparsity in Multivariate Extremes with Applications to Anomaly Detection
... work of Goix et al. (2015), where non-asymptotic bounds related to the statistical performance of a non-parametric estimator of the STDF, another functional measure of the dependence ... Voir le document complet
58
Sparse and low-rank multivariate Hawkes processes
... events of users (referred to as nodes in the following) that are fully identified through their corresponding user id and ...structure of data consisting in a sequence of independent cascades, ... Voir le document complet
33
Finite-Sample Diagnostics for Multivariate Regressions with Applications to Linear Asset Pricing Models
... free of nuisance parameters; see, for example, Godfrey (1988), Richardson and Smith (1993) and the recent litera- ture on multivariate GARCH, which may be traced back to Engle and Kroner (1995) and ... Voir le document complet
36
Depth-based multivariate descriptive statistics with hydrological applications
... Figure 6: Half-space depth evaluation for the point θ in an arbitrary generated sample. The numbers in boxes represent 818 the number of points in the associated half-space. The minimum value is 2 which gives the ... Voir le document complet
50
Bayesian Dirichlet mixture model for multivariate extremes: a re-parametrization
... HAL Id: hal-00880879 https://hal.archives-ouvertes.fr/hal-00880879 Submitted on 11 Nov 2013 HAL is a multi-disciplinary open access archive for the deposit and dissemination of sci- entific research documents, ... Voir le document complet
52
Polynomial equivalence problems and applications to multivariate cryptosystems
... Unité de recherche INRIA Rocquencourt Domaine de Voluceau - Rocquencourt - BP 105 - 78153 Le Chesnay Cedex France Unité de recherche INRIA Futurs : Domaine de Voluceau - Rocquencourt - B[r] ... Voir le document complet
26
Bayesian Sparse Fourier Representation of Off-Grid Targets
... values of mismatch and post-processing SNR (defined in ...case of low power, and a Gaussian distribution in the case of high ...proposal to a Gaussian proposal (and vice-versa) depending on ... Voir le document complet
7
Optimization of Perron eigenvectors and applications: from web ranking to chronotherapeutics
... sands of artificial pages pointing to the page they wanted to promote ...link-based ranking algorithms were developed: Brin and Page’s PageRank and Kleinberg’s ...core of the search ... Voir le document complet
193
On Loss Functions and Ranking Forecasting Performances of Multivariate Volatility Models
... 1987 to June 30, 2004 ...Days with too many missing values and/or constant prices are also ...difference of the logarithmic ...1987 to December 28, 2001 (3666 trading days), while the remaining ... Voir le document complet
63
On Loss Functions and Ranking Forecasting Performances of Multivariate Volatility Models
... evaluation of the forecasting performance of volatility models raises the problem that the variable of interest ...evaluation of the loss function has to rely on a ...distortion ... Voir le document complet
65
Sparse Interpolation in Terms of Multivariate Chebyshev Polynomials
... forebear of our algorithm is Prony’s method to retrieve a univariate function as a linear combination of exponential functions from its values at equally spaced points [ 51 ...some of the ... Voir le document complet
50
Finite-Sample Diagnostics for Multivariate Regressions with Applications to Linear Asset Pricing Models
... applied to a typical multivariate market-model based on New York Stock Exchange (NYSE) portfolios, constructed from the University of Chicago Center for Research in Security Prices (CRSP) data base ... Voir le document complet
37
A multivariate representation of compressed pin-by-pin cross sections
... difficult to compare the applications of the same interpolation problem separately on the set of original cross sections and on the set of their compressed coeffi- cients, because each ... Voir le document complet
14
Fusion of multispectral and hyperspectral images based on sparse representation
... the sparse code, and ¯ U is the ap- proximation of U derived from the dictionary and the ...many applications, the dictionary D is •xed a priori, and corresponds to various types of ... Voir le document complet
7
Fusion of multispectral and hyperspectral images based on sparse representation
... left to right): RMSE, UIQI, SAM and DD. of the target image can be represented by the atoms learned from the observed ...by sparse coding. The target image and the values of the code were then ... Voir le document complet
6
Seq2VAR: multivariate time series representation with relational neural networks and linear autoregressive model
... tion of multivariate time series (MTS) is a difficult task, since informa- tion is entangled both in temporal and spatial ...observation of simultaneous causal interactions between dynamical ...way ... Voir le document complet
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