1 citations · 1 across the 2 of their papers we have counts for
7 papers
Model Selection for SLOPE Models: A Bayesian Perspective
Fabio Feser, Marina Evangelou
Sorted Penalized Estimation (SLOPE) models, that perform either variable or group selection, control the false discovery rate (FDR) under orthogonal settings with known no…
Multi-view biclustering via non-negative matrix tri-factorisation
Ella S. C. Orme, Theodoulos Rodosthenous, Marina Evangelou
Multi-view data is ever more apparent as methods for production, collection and storage of data become more feasible both practically and fiscally. However, not all features are re…
Group Spike and Slab Variational Bayes
Michael Komodromos, Marina Evangelou, Sarah Filippi +1
We introduce Group Spike-and-slab Variational Bayes (GSVB), a scalable method for group sparse regression. A fast co-ordinate ascent variational inference (CAVI) algorithm is devel…
Dual Feature Reduction for the Sparse-group Lasso and its Adaptive Variant
Fabio Feser, Marina Evangelou
The sparse-group lasso performs both variable and group selection, simultaneously using the strengths of the lasso and group lasso. It has found widespread use in genetics, a field…
Strong Screening Rules for Group-based SLOPE Models
Fabio Feser, Marina Evangelou
Tuning the regularization parameter in penalized regression models is an expensive task, requiring multiple models to be fit along a path of parameters. Strong screening rules dras…
Correlating Variational Autoencoders Natively For Multi-View Imputation
Ella S. C. Orme, Marina Evangelou, Ulrich Paquet
Multi-view data from the same source often exhibit correlation. This is mirrored in correlation between the latent spaces of separate variational autoencoders (VAEs) trained on eac…