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NIPS
2007
13 years 9 months ago
DIFFRAC: a discriminative and flexible framework for clustering
We present a novel linear clustering framework (DIFFRAC) which relies on a linear discriminative cost function and a convex relaxation of a combinatorial optimization problem. The...
Francis Bach, Zaïd Harchaoui
SDM
2007
SIAM
117views Data Mining» more  SDM 2007»
13 years 9 months ago
Discriminating Subsequence Discovery for Sequence Clustering
In this paper, we explore the discriminating subsequencebased clustering problem. First, several effective optimization techniques are proposed to accelerate the sequence mining p...
Jianyong Wang, Yuzhou Zhang, Lizhu Zhou, George Ka...
DIS
2010
Springer
13 years 6 months ago
ESTATE: Strategy for Exploring Labeled Spatial Datasets Using Association Analysis
Abstract. We propose an association analysis-based strategy for exploration of multi-attribute spatial datasets possessing naturally arising classification. Proposed strategy, EST...
Tomasz F. Stepinski, Josue Salazar, Wei Ding 0003,...
ICCV
2007
IEEE
14 years 9 months ago
Classification of Weakly-Labeled Data with Partial Equivalence Relations
In many vision problems, instead of having fully labeled training data, it is easier to obtain the input in small groups, where the data in each group is constrained to be from th...
Sanjiv Kumar, Henry A. Rowley
CVPR
2006
IEEE
14 years 9 months ago
Kernel Uncorrelated and Orthogonal Discriminant Analysis: A Unified Approach
Several kernel algorithms have recently been proposed for nonlinear discriminant analysis. However, these methods mainly address the singularity problem in the high dimensional fe...
Tao Xiong, Jieping Ye, Vladimir Cherkassky