Search results for "lasso"

Metafysiikan uskonnollinen loppu? : Meillassoux ja fideismi

2019

Artikkeli käy lyhyesti läpi Quentin Meillassoux’n Äärellisyyden jälkeen -teoksessa esittelemiä spekulatiivisen materialismin lähtökohtia: ajatuksen Kantin jälkeistä filosofiasta hallinneesta korrelationismista ja sen ”heikosta” ja ”vahvasta” muodosta sekä Meillassoux’n perusargumentin, jolla hän pyrkii osoittamaan vahvan korrelationismin pyrkimyksen absoluuttisista viitepiisteistä luopumiseen sisäisesti ristiriitaiseksi. Tarkastelun pääpaino on kuitenkin Meillassoux’n väitteessä, että ajattelun riisuminen kaikista absoluuttisista näkökohdista johtaa vahvan korrelationismin omaksumaan ”fideistisen”, uskon ja järjen erillisyyttä ja keskinäistä riippumattomuutta korostavan suhtautumisen uskonn…

INDAGINI SPETTROSCOPICHE SU PRODOTTI LATTIERO-CASEARI: UN APPROCCIO CHEMIOMETRICO ALLA TRACCIABILITÀ

Tuning parameter selection in LASSO regression

2016

We propose a new method to select the tuning parameter in lasso regression. Unlike the previous proposals, the method is iterative and thus it is particularly efficient when multiple tuning parameters have to be selected. The method also applies to more general regression frameworks, such as generalized linear models with non-normal responses. Simulation studies show our proposal performs well, and most of times, better when compared with the traditional Bayesian Information Criterion and Cross validation.

Covariate adjusted censored gaussian lasso estimator

2021

The covariate adjusted glasso is one of the most used estimators for in- ferring genetic networks. Despite its diffusion, there are several fields in applied research where the limits of detection of modern measurement technologies make the use of this estimator theoretically unfounded, even when the assumption of a multivariate Gaussian distribution is satisfied. In this paper we propose an extension to censored data.

SPARSE INFERENCE IN COVARIATE ADJUSTED CENSORED GAUSSIAN GRAPHICAL MODELS

2021

The covariate adjusted glasso is one of the most used estimators for inferring genetic networks. Despite its diffusion, there are several fields in applied research where the limits of detection of modern measurement technologies make the use of this estimator theoretically unfounded, even when the assumption of a multivariate Gaussian distribution is satisfied. In this paper we propose an extension to censored data.

A computational method to estimate sparse multiple Gaussian graphical models

2012

In recent years several researchers have proposed the use of the Gaussian graphical model defined on a high dimensional setting to explore the dependence relationships between random variables. Standard methods, usually proposed in literature, are based on the use of a specific penalty function, such as the L1-penalty function. In this paper our aim is to estimate and compare two or more Gaussian graphical models defined in a high dimensional setting. In order to accomplish our aim, we propose a new computational method, based on glasso method, which lets us to extend the notion of p-value.

The Joint Censored Gaussian Graphical Lasso Model

2022

The Gaussian graphical model is one of the most used tools for inferring genetic networks. Nowadays, the data are often collected from different sources or under different biological conditions, resulting in heterogeneous datasets that exhibit a dependency structure that varies across groups. The complex structure of these data is typically recovered using regularized inferential procedures that use two penalties, one that encourages sparsity within each graph and the other that encourages common structures among the different groups. To this date, these approaches have not been developed for handling the case of censored data. However, these data are often generated by gene expression tech…

Geografie del collasso. L'Antropocene in 9 parole chiave

2021

Covid-19 è il primo grande trauma collettivo dell’Antropocene, una catena di eventi materiali, culturali e sociali che stanno aggredendo il nostro immaginario con un impatto incalcolabile. Un effetto profondo della pandemia sarà costringere l’umanità al prossimo step cognitivo: l’accettazione della fine della pace climatica dell’Olocene. Abbiamo bisogno di tempo, ma il tempo a disposizione è poco. Negare il trauma, fare come l’erbivoro assalito dalla belva che si anestetizza per non vedere la fine è qualcosa che non possiamo permetterci. Dissoluzione degli ecosistemi terrestri, questione animale, mutamento climatico, inquinamento e dissesto demografico, diaspora, populismo, suprematismo, er…

Il Mediterraneo di Giuseppe Galasso

2018

La visione del Mediterraneo di Giuseppe Galasso, uno dei maggiori storici italiani contemporanei, recentemente scomparso, che ha dedicato all’argomento diverse pagine su questa rivista, attraversandolo diacronicamente dall’antichità sino ai nostri giorni. The Mediterranean vision of one of the most important contemporary italian historians, recently deceased, who dedicated several pages on the subject in this journal, with a diachronic approach from antiquity to the present day

An efficient algorithm to estimate the sparse group structure of an high-dimensional generalized linear model

2014

Massive regression is one of the new frontiers of computational statistics. In this paper we propose a generalization of the group least angle regression method based on the differential geometrical structure of a generalized linear model specified by a fixed and known group structure of the predictors. An efficient algorithm is also proposed to compute the proposed solution curve.