Mar 31, 2015 · Our approach is based on reformulating a cardinality-constrained problem exactly as a Boolean pro- gram, to which standard convex relaxations ...
Mar 31, 2015 · In this paper, we first showed how a broad class of cardinality-constrained (or penalized) sparse learning problems can be reformulated exactly ...
Sparse learning via Boolean relaxations · Download: .pdf · Authors: Mert Pilanci, Martin J. Wainwright and Laurent El Ghaoui. · Status: Published in ·ath.
Novel relaxations for cardinality-constrained learning problems, including least-squares regression as a special but important case, and it is shown that ...
Feb 1, 2023 · The paper presents an algorithm for learning sparse group models. The key technique used is a convex Boolean relaxation. Solution to the ...
We introduce novel relaxations for cardinality-constrained learning problems, including least-squares regression as a special but important case.
Abstract: We introduce novel relaxations for cardinality-constrained learning problems, including least-squares regression as a special but important case.
Novel framework for sparse group models. ○ Theoretically for two random ensembles,. ○ achieve the exactness with high probability. ○ achieve nearly optimal ...
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ABSTRACT. We introduce an efficient algorithmic framework for learning sparse group models formulated as the natural convex relaxation of a ...
This paper develops a novel optimization framework for learning accurate and sparse two-level Boolean rules for classification, both in Conjunctive Normal ...
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