TY - GEN
T1 - Provable Imbalanced Point Clustering
AU - Denisov, David
AU - Feldman, Dan
AU - Dolev, Shlomi
AU - Segal, Michael
N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
PY - 2024/12/31
Y1 - 2024/12/31
N2 - We suggest efficient and provable methods to compute an approximation for imbalanced point clustering, that is, fitting k-centers to a set of points in Rd, for any d,k≥1. To this end, we utilize coresets, which, in the context of the paper, are essentially weighted sets of points in Rd that approximate the fitting loss for every model in a given set, up to a multiplicative factor of 1±ε. In Sect. 3 we provide experiments that show the empirical contribution of our suggested methods for real images (novel and reference), synthetic data, and real-world data. We also propose choice clustering, which by combining clustering algorithms yields better performance than each one separately.
AB - We suggest efficient and provable methods to compute an approximation for imbalanced point clustering, that is, fitting k-centers to a set of points in Rd, for any d,k≥1. To this end, we utilize coresets, which, in the context of the paper, are essentially weighted sets of points in Rd that approximate the fitting loss for every model in a given set, up to a multiplicative factor of 1±ε. In Sect. 3 we provide experiments that show the empirical contribution of our suggested methods for real images (novel and reference), synthetic data, and real-world data. We also propose choice clustering, which by combining clustering algorithms yields better performance than each one separately.
UR - http://www.scopus.com/inward/record.url?scp=85214192610&partnerID=8YFLogxK
U2 - https://doi.org/10.1007/978-3-031-76934-4_5
DO - https://doi.org/10.1007/978-3-031-76934-4_5
M3 - Conference contribution
SN - 9783031769337
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 79
EP - 91
BT - Cyber Security, Cryptology, and Machine Learning - 8th International Symposium, CSCML 2024, Proceedings
A2 - Dolev, Shlomi
A2 - Elhadad, Michael
A2 - Kutyłowski, Mirosław
A2 - Persiano, Giuseppe
PB - Springer Science and Business Media Deutschland GmbH
T2 - 8th International Symposium on Cyber Security, Cryptology, and Machine Learning, CSCML 2024
Y2 - 19 December 2024 through 20 December 2024
ER -