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TKDE
2012
245views Formal Methods» more  TKDE 2012»
9 years 3 months ago
Semi-Supervised Maximum Margin Clustering with Pairwise Constraints
—The pairwise constraints specifying whether a pair of samples should be grouped together or not have been successfully incorporated into the conventional clustering methods such...
Hong Zeng, Yiu-ming Cheung
DAGM
2011
Springer
10 years 1 months ago
Putting MAP Back on the Map
Conditional Random Fields (CRFs) are popular models in computer vision for solving labeling problems such as image denoising. This paper tackles the rarely addressed but important ...
Patrick Pletscher, Sebastian Nowozin, Pushmeet Koh...
ICASSP
2011
IEEE
10 years 5 months ago
Maximum margin structure learning of Bayesian network classifiers
Recently, the margin criterion has been successfully used for parameter optimization in graphical models. We introduce maximum margin based structure learning for Bayesian network...
Franz Pernkop, Michael Wohlmay, Manfred Mücke
ICDM
2010
IEEE
200views Data Mining» more  ICDM 2010»
10 years 10 months ago
Bayesian Maximum Margin Clustering
Abstract--Most well-known discriminative clustering models, such as spectral clustering (SC) and maximum margin clustering (MMC), are non-Bayesian. Moreover, they merely considered...
Bo Dai, Baogang Hu, Gang Niu
ICDM
2009
IEEE
175views Data Mining» more  ICDM 2009»
10 years 11 months ago
Maximum Margin Clustering with Multivariate Loss Function
This paper presents a simple but powerful extension of the maximum margin clustering (MMC) algorithm that optimizes multivariate performance measure specifically defined for clust...
Bin Zhao, James Tin-Yau Kwok, Changshui Zhang
JMLR
2010
123views more  JMLR 2010»
10 years 11 months ago
Maximum Relative Margin and Data-Dependent Regularization
Leading classification methods such as support vector machines (SVMs) and their counterparts achieve strong generalization performance by maximizing the margin of separation betw...
Pannagadatta K. Shivaswamy, Tony Jebara
NIPS
2004
11 years 2 months ago
Maximum Margin Clustering
We propose a new method for clustering based on finding maximum margin hyperplanes through data. By reformulating the problem in terms of the implied equivalence relation matrix, ...
Linli Xu, James Neufeld, Bryce Larson, Dale Schuur...
SDM
2008
SIAM
161views Data Mining» more  SDM 2008»
11 years 2 months ago
Efficient Maximum Margin Clustering via Cutting Plane Algorithm
Maximum margin clustering (MMC) is a recently proposed clustering method, which extends the theory of support vector machine to the unsupervised scenario and aims at finding the m...
Bin Zhao, Fei Wang, Changshui Zhang
COLT
2003
Springer
11 years 6 months ago
Maximum Margin Algorithms with Boolean Kernels
Recent work has introduced Boolean kernels with which one can learn linear threshold functions over a feature space containing all conjunctions of length up to k (for any 1 ≤ k ...
Roni Khardon, Rocco A. Servedio
ICML
2007
IEEE
12 years 2 months ago
Approximate maximum margin algorithms with rules controlled by the number of mistakes
We present a family of incremental Perceptron-like algorithms (PLAs) with margin in which both the "effective" learning rate, defined as the ratio of the learning rate t...
Petroula Tsampouka, John Shawe-Taylor
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