TY - GEN
T1 - Multiclass MinMax rank aggregation
AU - Li, Pan
AU - Milenkovic, Olgica
N1 - Publisher Copyright:
© 2017 IEEE.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2017/8/9
Y1 - 2017/8/9
N2 - We introduce a new family of minmax rank aggregation problems under two distance measures, the Kendall τ and the Spearman footrule. As the problems are NP-hard, we proceed to describe a number of constant-approximation algorithms for solving them. We conclude with illustrative applications of the aggregation methods on the Mallows model and genomic data.
AB - We introduce a new family of minmax rank aggregation problems under two distance measures, the Kendall τ and the Spearman footrule. As the problems are NP-hard, we proceed to describe a number of constant-approximation algorithms for solving them. We conclude with illustrative applications of the aggregation methods on the Mallows model and genomic data.
UR - http://www.scopus.com/inward/record.url?scp=85034059795&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85034059795&partnerID=8YFLogxK
U2 - 10.1109/ISIT.2017.8007080
DO - 10.1109/ISIT.2017.8007080
M3 - Conference contribution
AN - SCOPUS:85034059795
T3 - IEEE International Symposium on Information Theory - Proceedings
SP - 3000
EP - 3004
BT - 2017 IEEE International Symposium on Information Theory, ISIT 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE International Symposium on Information Theory, ISIT 2017
Y2 - 25 June 2017 through 30 June 2017
ER -