Tilbake til alle arrangementer

Seminar Series in Statistics and Data Science: Valeria Vitelli

After a break, we are extremely pleased to invite you again to our Tuesday seminar of

Seminar series in Statistics and Data Science

Speaker:  Valeria Vitelli, Associate Professor, Department of Biostatistics, University of Oslo

Title: Rank-based covariate-informed clustering of high-dimensional data with variable selection

When? Tuesday 31.10.2023, 14:15-15:15

Where?  Erling Svedrups plass and Zoom 

https://uio.zoom.us/j/66849037258?pwd=NkNiR0lkbm5VK0VyMytVZW4vV0hNQT09

Abstract

Rank-based models can be used to estimate individual behaviours and preferences in several areas, such as marketing and politics. Often, combining the expressed preferences with additional user-related information (covariates) can potentially lead to a better accuracy in individual predictions, by enhancing the understanding of the users’ personal profiles. The Mallows model is a popular model for rankings, as it flexibly adapts to different types of preference data, and the previously proposed Bayesian Mallows Model (BMM) offers a computationally efficient framework for Bayesian inference also allowing capturing the users’ heterogeneity, via a finite mixture. However, the Mallows model does not seem realistic when the pool of items is large, and furthermore BMM does not currently allow the use of covariates. In this talk, I will introduce a recent extension of BMM that embeds covariate information in a joint rank-based clustering framework. The proposed method is based on a similarity function that a priori favours the aggregation of people into a cluster when their covariates are similar. A lower-dimensional version of BMM (lowBMM) that scales to large datasets has also been proposed and used in the context of cancer genomics; however, lowBMM does not perform clustering. We now propose to combine the Bayesian mixture of Mallows models with items selection, to jointly perform variable selection and clustering. Performance of both methods is investigated via simulation studies, and real-data examples in genomics and preference learning are also shown. This is joint work with Emilie Eliseussen, Arnoldo Frigessi, Haakon Muggerud, Ida Scheel.  

 Welcome!

 Best regards,

Sven Ove Samuelsen & Aliaksandr Hubin

Tidligere arrangement: 24. oktober
Explaining AI-seminar
Senere arrangement: 9. november
OCBE Biostatisctis Seminar: Antonio Canale