A new algorithm, TS-CRR, solves anomaly-filtered sparse polynomial regression through a MILP-to-QCQP-to-fractional-program reformulation with conic relaxation, claiming better computational properties and good benchmark results.
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Sparse Polynomial Regression under Anomalous Data
A new algorithm, TS-CRR, solves anomaly-filtered sparse polynomial regression through a MILP-to-QCQP-to-fractional-program reformulation with conic relaxation, claiming better computational properties and good benchmark results.