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ICPR
2008
IEEE
15 years 8 months ago
A supervised learning approach for imbalanced data sets
This paper presents a new learning approach for pattern classification applications involving imbalanced data sets. In this approach, a clustering technique is employed to resamp...
Giang Hoang Nguyen, Abdesselam Bouzerdoum, Son Lam...
ICPR
2002
IEEE
15 years 6 months ago
Hierarchical Interpretation of Human Activities Using Competitive Learning
In this paper we describe a method of learning hierarchical representations for describing and recognizing gestures expressed as one and two arm movements using competitive learni...
Harry Wechsler, Zoran Duric, Fayin Li
ICCV
2009
IEEE
1556views Computer Vision» more  ICCV 2009»
16 years 6 months ago
Kernel Methods for Weakly Supervised Mean Shift Clustering
Mean shift clustering is a powerful unsupervised data analysis technique which does not require prior knowledge of the number of clusters, and does not constrain the shape of th...
Oncel Tuzel, Fatih Porikli, Peter Meer
SDM
2009
SIAM
152views Data Mining» more  SDM 2009»
15 years 11 months ago
Multiple Kernel Clustering.
Maximum margin clustering (MMC) has recently attracted considerable interests in both the data mining and machine learning communities. It first projects data samples to a kernel...
Bin Zhao, James T. Kwok, Changshui Zhang
GECCO
2007
Springer
209views Optimization» more  GECCO 2007»
15 years 8 months ago
Kernel based automatic clustering using modified particle swarm optimization algorithm
This paper introduces a method for clustering complex and linearly non-separable datasets, without any prior knowledge of the number of naturally occurring clusters. The proposed ...
Ajith Abraham, Swagatam Das, Amit Konar