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ICDM
2009
IEEE
117views Data Mining» more  ICDM 2009»
14 years 2 months ago
Discriminative Mixed-Membership Models
Although mixed-membership models have achieved great success in unsupervised learning, they have not been widely applied to classification problems. In this paper, we propose a f...
Hanhuai Shan, Arindam Banerjee, Nikunj C. Oza
PKDD
2009
Springer
152views Data Mining» more  PKDD 2009»
14 years 2 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
ICDM
2003
IEEE
181views Data Mining» more  ICDM 2003»
14 years 1 months ago
Dynamic Weighted Majority: A New Ensemble Method for Tracking Concept Drift
Algorithms for tracking concept drift are important for many applications. We present a general method based on the Weighted Majority algorithm for using any online learner for co...
Jeremy Z. Kolter, Marcus A. Maloof
AUSDM
2006
Springer
112views Data Mining» more  AUSDM 2006»
13 years 11 months ago
Accuracy Estimation With Clustered Dataset
If the dataset available to machine learning results from cluster sampling (e.g. patients from a sample of hospital wards), the usual cross-validation error rate estimate can lead...
Ricco Rakotomalala, Jean-Hugues Chauchat, Fran&cce...
PKDD
2009
Springer
103views Data Mining» more  PKDD 2009»
14 years 2 months ago
Kernels for Periodic Time Series Arising in Astronomy
Abstract. We present a method for applying machine learning algorithms to the automatic classification of astronomy star surveys using time series of star brightness. Currently su...
Gabriel Wachman, Roni Khardon, Pavlos Protopapas, ...