Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
A parameterized complexity analysis of combinatorial feature selection problems. / Froese, Vincent; Van Bevern, René; Niedermeier, Rolf и др.
Mathematical Foundations of Computer Science 2013 - 38th International Symposium, MFCS 2013, Proceedings. 2013. стр. 445-456 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Том 8087 LNCS).Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
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TY - GEN
T1 - A parameterized complexity analysis of combinatorial feature selection problems
AU - Froese, Vincent
AU - Van Bevern, René
AU - Niedermeier, Rolf
AU - Sorge, Manuel
PY - 2013/10/15
Y1 - 2013/10/15
N2 - We examine the algorithmic tractability of NP-hard combinatorial feature selection problems in terms of parameterized complexity theory. In combinatorial feature selection, one seeks to discard dimensions from high-dimensional data such that the resulting instances fulfill a desired property. In parameterized complexity analysis, one seeks to identify relevant problem-specific quantities and tries to determine their influence on the computational complexity of the considered problem. In this paper, for various combinatorial feature selection problems, we identify parameterizations and reveal to what extent these govern computational complexity. We provide tractability as well as intractability results; for example, we show that the Distinct Vectors problem on binary points is polynomial-time solvable if each pair of points differs in at most three dimensions, whereas it is NP-hard otherwise.
AB - We examine the algorithmic tractability of NP-hard combinatorial feature selection problems in terms of parameterized complexity theory. In combinatorial feature selection, one seeks to discard dimensions from high-dimensional data such that the resulting instances fulfill a desired property. In parameterized complexity analysis, one seeks to identify relevant problem-specific quantities and tries to determine their influence on the computational complexity of the considered problem. In this paper, for various combinatorial feature selection problems, we identify parameterizations and reveal to what extent these govern computational complexity. We provide tractability as well as intractability results; for example, we show that the Distinct Vectors problem on binary points is polynomial-time solvable if each pair of points differs in at most three dimensions, whereas it is NP-hard otherwise.
UR - http://www.scopus.com/inward/record.url?scp=84885194986&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-40313-2_40
DO - 10.1007/978-3-642-40313-2_40
M3 - Conference contribution
AN - SCOPUS:84885194986
SN - 9783642403125
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 445
EP - 456
BT - Mathematical Foundations of Computer Science 2013 - 38th International Symposium, MFCS 2013, Proceedings
T2 - 38th International Symposium on Mathematical Foundations of Computer Science, MFCS 2013
Y2 - 26 August 2013 through 30 August 2013
ER -
ID: 22340869