• Aucun résultat trouvé

Lasso and probabilistic inequalities for multivariate point processes

N/A
N/A
Protected

Academic year: 2021

Partager "Lasso and probabilistic inequalities for multivariate point processes"

Copied!
62
0
0

Texte intégral

Figure

Figure 1. Raster plots of two data sets with T = 2 corresponding to Experiment 2 on the left and Experiment 3 on the right
Figure 2. Reconstructions corresponding to Experiment 2 with the OLS estimate with T = 2 and K = 8
Figure 3. Reconstructions corresponding to Experiment 2 with T = 2 and K = 8. Each line m represents the function h (m) ` , for ` = 1,2
Figure 4. Reconstructions corresponding to Experiment 2 with T = 20 and K = 8. Same convention
+2

Références

Documents relatifs

This paper defines an information flow control model, namely Tuple-Based Access Control (TBAC), inspired by lattice-based and Mandatory Access Control (MAC) models [23] as well as

To our knowledge there are only two non asymptotic results for the Lasso in logistic model : the first one is from Bach [2], who provided bounds for excess risk

To our knowledge there are only two non asymptotic results for the Lasso in logistic model: the first one is from Bach [2], who provided bounds for excess risk

In this paper, we prove a process-level, also known as level-3 large deviation principle for a very general class of simple point processes, i.e.. nonlinear Hawkes process, with a

Davydov’s inequality has the following known application to the control of the variance of partial sums of strongly mixing arrays of real-valued random variables. 0)

In the whole paper (X i ) 16i6n is a sequence of centred random variables. We shall obtain here a value of ρ which depends on conditional moments of the variables. We also want

Using large deviation techniques, it is shown that T c I is equivalent to some concentration inequality for the occupation measure of a µ- reversible ergodic Markov process related

A multivariate Hawkes framework is proposed to model the clustering and autocorrelation of times of cyber attacks in the different group.. In this section we present the model and