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» Theoretical Frameworks for Data Mining
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WSDM
2010
ACM
204views Data Mining» more  WSDM 2010»
14 years 4 months ago
Learning URL patterns for webpage de-duplication
Presence of duplicate documents in the World Wide Web adversely affects crawling, indexing and relevance, which are the core building blocks of web search. In this paper, we pres...
Hema Swetha Koppula, Krishna P. Leela, Amit Agarwa...
PKDD
2009
Springer
103views Data Mining» more  PKDD 2009»
14 years 3 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, ...
SDM
2007
SIAM
120views Data Mining» more  SDM 2007»
13 years 10 months ago
An Analysis of Logistic Models: Exponential Family Connections and Online Performance
Logistic models are arguably one of the most widely used data analysis techniques. In this paper, we present analyses focussing on two important aspects of logistic models—its r...
Arindam Banerjee
PKDD
2010
Springer
179views Data Mining» more  PKDD 2010»
13 years 7 months ago
Gaussian Processes for Sample Efficient Reinforcement Learning with RMAX-Like Exploration
Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...
Tobias Jung, Peter Stone
SDM
2011
SIAM
233views Data Mining» more  SDM 2011»
13 years 21 hour ago
Multi-Instance Mixture Models
Multi-instance (MI) learning is a variant of supervised learning where labeled examples consist of bags (i.e. multi-sets) of feature vectors instead of just a single feature vecto...
James R. Foulds, Padhraic Smyth