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ICDM
2006
IEEE
225views Data Mining» more  ICDM 2006»
16 years 1 months ago
Adaptive Kernel Principal Component Analysis with Unsupervised Learning of Kernels
Choosing an appropriate kernel is one of the key problems in kernel-based methods. Most existing kernel selection methods require that the class labels of the training examples ar...
Daoqiang Zhang, Zhi-Hua Zhou, Songcan Chen
ICDM
2006
IEEE
183views Data Mining» more  ICDM 2006»
16 years 1 months ago
Accelerating Newton Optimization for Log-Linear Models through Feature Redundancy
— Log-linear models are widely used for labeling feature vectors and graphical models, typically to estimate robust conditional distributions in presence of a large number of pot...
Arpit Mathur, Soumen Chakrabarti
ICDM
2006
IEEE
119views Data Mining» more  ICDM 2006»
16 years 1 months ago
Direct Marketing When There Are Voluntary Buyers
1 In traditional direct marketing, the implicit assumption is that customers will only purchase the product if they are contacted. In real business environments, however, there ar...
Yi-Ting Lai, Ke Wang, Daymond Ling, Hua Shi, Jason...
ICDM
2006
IEEE
182views Data Mining» more  ICDM 2006»
16 years 1 months ago
Active Learning to Maximize Area Under the ROC Curve
In active learning, a machine learning algorithm is given an unlabeled set of examples U, and is allowed to request labels for a relatively small subset of U to use for training. ...
Matt Culver, Kun Deng, Stephen D. Scott
ICDM
2006
IEEE
151views Data Mining» more  ICDM 2006»
16 years 1 months ago
Decision Trees for Functional Variables
Classification problems with functionally structured input variables arise naturally in many applications. In a clinical domain, for example, input variables could include a time...
Suhrid Balakrishnan, David Madigan