Semi-Definite Programming Task: Difference between revisions
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<B>See:</B> [[Definite Programming]], [[Linear Programming]]. | <B>See:</B> [[Definite Programming]], [[Linear Programming]], [[Eigenvalue Decomposition]]. | ||
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== References == | |||
=== 2006 === | |||
* ([[2014_EffectiveGlobalApproachesforMut|Nguyen et al., 2014]]) ⇒ [[Xuan Vinh Nguyen]], [[Jeffrey Chan]], [[Simone Romano]], and [[James Bailey]]. ([[2014]]). “Effective Global Approaches for Mutual Information based Feature Selection.” In: [[Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining]] ([[KDD-2014]]) Journal. ISBN:978-1-4503-2956-9 [http://dx.doi.org/10.1145/2623330.2623611 doi:10.1145/2623330.2623611] | |||
** QUOTE: [[In this paper, we]] take a [[systematic approach]] to the [[problem of global MI-based feature selection]]. </s> [[We]] show how the resulting [[NP-hard]] [[global optimization problem]] could be [[efficiently approximately solved]] via [[spectral relaxation]] and [[semi-definite programming technique]]s. </s> | |||
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Latest revision as of 20:56, 23 September 2021
See: Definite Programming, Linear Programming, Eigenvalue Decomposition.
References
2006
- (Nguyen et al., 2014) ⇒ Xuan Vinh Nguyen, Jeffrey Chan, Simone Romano, and James Bailey. (2014). “Effective Global Approaches for Mutual Information based Feature Selection.” In: Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2014) Journal. ISBN:978-1-4503-2956-9 doi:10.1145/2623330.2623611
- QUOTE: In this paper, we take a systematic approach to the problem of global MI-based feature selection. We show how the resulting NP-hard global optimization problem could be efficiently approximately solved via spectral relaxation and semi-definite programming techniques.