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DATAMINE
1999
108views more  DATAMINE 1999»
15 years 7 months ago
A Survey of Methods for Scaling Up Inductive Algorithms
Abstract. One of the de ning challenges for the KDD research community is to enable inductive learning algorithms to mine very large databases. This paper summarizes, categorizes, ...
Foster J. Provost, Venkateswarlu Kolluri
ML
2002
ACM
220views Machine Learning» more  ML 2002»
15 years 7 months ago
Bayesian Methods for Support Vector Machines: Evidence and Predictive Class Probabilities
I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...
Peter Sollich
ML
1998
ACM
139views Machine Learning» more  ML 1998»
15 years 7 months ago
The Hierarchical Hidden Markov Model: Analysis and Applications
We introduce, analyze and demonstrate a recursive hierarchical generalization of the widely used hidden Markov models, which we name Hierarchical Hidden Markov Models (HHMM). Our m...
Shai Fine, Yoram Singer, Naftali Tishby
SAC
2002
ACM
15 years 7 months ago
Color patterns for pictorial content description
In this paper, we propose a new type of image feature, which consists of patterns of colors and intensities that capture the latent associations among images and primitive feature...
Daniela Stan, Ishwar K. Sethi
SIGIR
2002
ACM
15 years 7 months ago
Liberal relevance criteria of TREC -: counting on negligible documents?
Most test collections (like TREC and CLEF) for experimental research in information retrieval apply binary relevance assessments. This paper introduces a four-point relevance scal...
Eero Sormunen
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