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258
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PAKDD
2011
ACM
473views Data Mining» more  PAKDD 2011»
14 years 9 months ago
 Finding Rare Classes: Adapting Generative and Discriminative Models in Active Learning
Discovering rare categories and classifying new instances of them is an important data mining issue in many fields, but fully supervised learning of a rare class classifier is pr...
Timothy Hospedales, Shaogang Gong and Tao Xiang
135
Voted
KDD
2002
ACM
110views Data Mining» more  KDD 2002»
16 years 4 months ago
A model for discovering customer value for E-content
There exists a huge demand for multimedia goods and services in the Internet. Currently available bandwidth speeds can support sale of downloadable content like CDs, e-books, etc....
Srinivasan Jagannathan, Jayanth Nayak, Kevin C. Al...
PKDD
2009
Springer
152views Data Mining» more  PKDD 2009»
15 years 10 months ago
Feature Selection for Value Function Approximation Using Bayesian Model Selection
Abstract. Feature selection in reinforcement learning (RL), i.e. choosing basis functions such that useful approximations of the unkown value function can be obtained, is one of th...
Tobias Jung, Peter Stone
106
Voted
PAKDD
2004
ACM
113views Data Mining» more  PAKDD 2004»
15 years 9 months ago
Logistic Regression and Boosting for Labeled Bags of Instances
Abstract. In this paper we upgrade linear logistic regression and boosting to multi-instance data, where each example consists of a labeled bag of instances. This is done by connec...
Xin Xu, Eibe Frank
119
Voted
SDM
2003
SIAM
125views Data Mining» more  SDM 2003»
15 years 5 months ago
Scalable, Balanced Model-based Clustering
This paper presents a general framework for adapting any generative (model-based) clustering algorithm to provide balanced solutions, i.e., clusters of comparable sizes. Partition...
Shi Zhong, Joydeep Ghosh