2026
Joint Model and Data Sparsification via the Marginal Likelihood
Alexander Timans, Thomas Moellenhoff, Christian Andersson Naesseth, Mohammad Emtiyaz Khan, Eric Nalisnick
ICML 2026poster
Sparse recovery in linear systems underpins applications from signal processing to high-dimensional regression. Sparse Bayesian Learning, grounded in the principle of automatic relevance determination (ARD), offers a practical Bayesian mechanism for feature sparsity via marginal likelihood optimizat…