TY - GEN
T1 - k-Means Clustering with Hölder Divergences
AU - Nielsen, Frank
AU - Sun, Ke
AU - Marchand-Maillet, Stéphane
N1 - KAUST Repository Item: Exported on 2020-10-01
PY - 2017/10/24
Y1 - 2017/10/24
N2 - We introduced two novel classes of Hölder divergences and Hölder pseudo-divergences that are both invariant to rescaling, and that both encapsulate the Cauchy-Schwarz divergence and the skew Bhattacharyya divergences. We review the elementary concepts of those parametric divergences, and perform a clustering analysis on two synthetic datasets. It is shown experimentally that the symmetrized Hölder divergences consistently outperform significantly the Cauchy-Schwarz divergence in clustering tasks.
AB - We introduced two novel classes of Hölder divergences and Hölder pseudo-divergences that are both invariant to rescaling, and that both encapsulate the Cauchy-Schwarz divergence and the skew Bhattacharyya divergences. We review the elementary concepts of those parametric divergences, and perform a clustering analysis on two synthetic datasets. It is shown experimentally that the symmetrized Hölder divergences consistently outperform significantly the Cauchy-Schwarz divergence in clustering tasks.
UR - http://hdl.handle.net/10754/626144
UR - https://link.springer.com/chapter/10.1007%2F978-3-319-68445-1_98
UR - http://www.scopus.com/inward/record.url?scp=85033662258&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-68445-1_98
DO - 10.1007/978-3-319-68445-1_98
M3 - Conference contribution
SN - 9783319684444
SP - 856
EP - 863
BT - Lecture Notes in Computer Science
PB - Springer Nature
ER -