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Found 11 papers, 4 papers with code
skscope: Fast Sparsity-Constrained Optimization in Python
Applying iterative solvers on sparsity-constrained optimization (SCO) requires tedious mathematical deduction and careful programming/debugging that hinders these solvers' broad impact.
A Consistent and Scalable Algorithm for Best Subset Selection in Single Index Models
SIMs provide an interpretable and flexible modeling framework for high-dimensional data, while best subset selection aims to find a sparse model from a large set of predictors.
Best-Subset Selection in Generalized Linear Models: A Fast and Consistent Algorithm via Splicing Technique
In high-dimensional generalized linear models, it is crucial to identify a sparse model that adequately accounts for response variation.
Simultaneous Best Subset Selection and Dimension Reduction via Primal-Dual Iterations
Sparse reduced rank regression is an essential statistical learning method.
Interpreting and predicting the economy flows: A time-varying parameter global vector autoregressive integrated the machine learning model
The paper proposes a time-varying parameter global vector autoregressive (TVP-GVAR) framework for predicting and analysing developed region economic variables.
The impact of spatio-temporal travel distance on epidemics using an interpretable attention-based sequence-to-sequence model
We unveil the geographical variations in the influence of population movement at different travel distances on the dynamics of epidemic spread.
abess: A Fast Best Subset Selection Library in Python and R
In addition, a user-friendly R library is available at the Comprehensive R Archive Network.
A Splicing Approach to Best Subset of Groups Selection
Best subset of groups selection (BSGS) is the process of selecting a small part of non-overlapping groups to achieve the best interpretability on the response variable.
Computational analysis of pathological image enables interpretable prediction for microsatellite instability
Microsatellite instability (MSI) is associated with several tumor types and its status has become increasingly vital in guiding patient treatment decisions.
A Fast and Effective Method of Macula Automatic Detection for Retina Images
Retina image processing is one of the crucial and popular topics of medical image processing.
Ball: An R package for detecting distribution difference and association in metric spaces
The rapid development of modern technology facilitates the appearance of numerous unprecedented complex data which do not satisfy the axioms of Euclidean geometry, while most of the statistical hypothesis tests are available in Euclidean or Hilbert spaces.
Computation
