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COLT
2008
Springer
13 years 11 months ago
Model Selection and Stability in k-means Clustering
Clustering Stability methods are a family of widely used model selection techniques applied in data clustering. Their unifying theme is that an appropriate model should result in ...
Ohad Shamir, Naftali Tishby
NIPS
2004
13 years 11 months ago
Boosting on Manifolds: Adaptive Regularization of Base Classifiers
In this paper we propose to combine two powerful ideas, boosting and manifold learning. On the one hand, we improve ADABOOST by incorporating knowledge on the structure of the dat...
Balázs Kégl, Ligen Wang
IDEAL
2007
Springer
14 years 3 months ago
Analysis of Tiling Microarray Data by Learning Vector Quantization and Relevance Learning
We apply learning vector quantization to the analysis of tiling microarray data. As an example we consider the classification of C. elegans genomic probes as intronic or exonic. T...
Michael Biehl, Rainer Breitling, Yang Li
SOCA
2007
IEEE
14 years 4 months ago
Context-aware Process Support through Automatic Selection and Invocation of Semantic Web Services
Current technologies aimed at supporting processes – whether it is a business process or a learning process – are usually based on using a dedicated set of metadata to describ...
Stefan Dietze, Alessio Gugliotta, John Domingue
AAAI
2008
14 years 23 hour ago
Adaptive Importance Sampling with Automatic Model Selection in Value Function Approximation
Off-policy reinforcement learning is aimed at efficiently reusing data samples gathered in the past, which is an essential problem for physically grounded AI as experiments are us...
Hirotaka Hachiya, Takayuki Akiyama, Masashi Sugiya...