sgs R package
An R package to fit sparse-group SLOPE (SGS) models.
An R package to fit sparse-group SLOPE (SGS) models.
An R package to fit sparse-group lasso (SGL) models using the dual feature reduction (DFR) approach.
Released in 2023
This paper presents a new high-dimensional approach for simultaneous variable and group selection, called Sparse-group SLOPE (SGS).
Recommended citation: Fabio Feser and Marina Evangelou (2023). "Sparse-group SLOPE: adaptive bi-level selection with FDR-control". arXiv preprint arXiv:2305.09467.
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Released in 2024
This paper presents strong screening rules for group SLOPE and sparse-group SLOPE. Accepted at AISTATS 25.
Recommended citation: Fabio Feser and Marina Evangelou (2025). "Strong screening rules for group-based SLOPE models". AISTATS 25, PMLR 258:352-360, 2025.
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Released in 2024
This paper presents a new feature reduction approach for the sparse-group lasso and adaptive sparse-group lasso, called Dual Feature Reduction (DFR). Accepted at ICML 25.
Recommended citation: Fabio Feser and Marina Evangelou (2024). "Dual feature reduction for the sparse-group lasso and its adaptive variant". arXiv preprint arXiv:2405.17094.
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Published:
Gave a talk on approaches for controlling the false-discovery rate (FDR) under high-dimensional settings. The talk was given to the Mary Lister scholars at Imperial College.
Published:
Discussed various approaches towards bi-level selection in a genetics framework, including sparse-group methods such as the sparse-group lasso and sparse-group SLOPE.
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Presented sparse-group SLOPE (SGS) at the CMStatistics 2023 conference.
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Presented a lecture on using penalised regression to perform disease prediction, as part of the Statistical Genetics module on the MSc Statistics at Imperial College.
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Invited talk to present ‘Sparse-group SLOPE: Adaptive bi-level selection with FDR-control’ during the ‘Reliable prediction models for challenging data’ session at COMPSTAT 2024.
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Presented a talk on adaptive sparse-group models at the UCPH Statistics Seminar at the University of Copenhagen.
Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.