SEMINARS IN STATISTICS @ COLLEGIO CARLO ALBERTO <https://www.google.com/url?q=https://www.carloalberto.org/events/category/seminars/seminars-in-statistics/page/2/?tribe-bar-date%3D2019-09-01&source=gmail-imap&ust=1732719071000000&usg=AOvVaw1_VfRy4qDP_HHioNc49JU_> Venerdì 19/12/2025, presso il Collegio Carlo Alberto, in Piazza Arbarello 8, Torino, si terrà il seguente seminario: ———————————————————————— 10.00-11.00 Speaker: Alejandra Avalos-Pacheco (JKU Linz) Title: Fast Integrative Factor Models: Applications from Nutritional Epidemiology to Cancer Genomics Abstract: Data-integration of multiple studies can be key to understand and gain knowledge in statistical research. However, such data present artifactual sources of variation, also known as covariate effects. Covariate effects can be complex, leading to systematic biases, that if not corrected could lead to unreliable inference. In this talk I will present novel sparse latent factor regression (FR) and multi-study factor regression (MSFR) models to integrate such heterogeneous data. The FR model provide a tool for data exploration via dimensionality reduction and sparse low-rank covariance estimation while correcting for a range of covariate effects. MSFR are extensions of FR that enable us to jointly obtain a covariance structure that models the group-specific covariances in addition to the common component. I will discuss the use of several sparse priors (local and non-local) to learn the dimension of the latent factors. Our approaches provide a flexible methodology for sparse factor regression which is not limited to data with covariate effects. Our models are fitted leveraging novel scalable EM and ECM algorithms as well as Variational Inference methods. I will present several examples, with a focus on bioinformatics applications. We show the usefulness of our methods in two main tasks: as an unsupervised dimension reduction task to give a visual representation of the latent factors of the data; and as a supervised tool to: (i) provide survival predictions leveraging the obtained factors, or (ii) obtain dietary patterns, associating each factor with a measure of overall diet quality related to cardiometabolic disease risk. ———————————————————————— Sarà possibile seguire il seminario anche in streaming: chiunque volesse collegarsi è pregato di inviare una email entro *mercoledì 17/12/2025* a matteo.giordano@unito.it <mailto:matteo.giordano@unito.it> Il webinar è organizzato dalla "de Castro" Statistics Initiative (www.carloalberto.org/stats <http://www.carloalberto.org/stats>) in collaborazione con il Collegio Carlo Alberto. Cordiali saluti, Matteo Giordano Assistant Professor (RTDA) Department of Economics, Social Studies, Applied Mathematics and Statistics (ESOMAS) www.matteogiordano.weebly.com <https://matteogiordano.weebly.com/>