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» A Study of Empirical Learning for an Involved Problem
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VLDB
2005
ACM
139views Database» more  VLDB 2005»
15 years 5 months ago
Statistical Learning Techniques for Costing XML Queries
Developing cost models for query optimization is significantly harder for XML queries than for traditional relational queries. The reason is that XML query operators are much mor...
Ning Zhang 0002, Peter J. Haas, Vanja Josifovski, ...
COLING
2010
14 years 6 months ago
Shallow Information Extraction from Medical Forum Data
We study a novel shallow information extraction problem that involves extracting sentences of a given set of topic categories from medical forum data. Given a corpus of medical fo...
Parikshit Sondhi, Manish Gupta, ChengXiang Zhai, J...
JMLR
2006
145views more  JMLR 2006»
14 years 11 months ago
Ensemble Pruning Via Semi-definite Programming
An ensemble is a group of learning models that jointly solve a problem. However, the ensembles generated by existing techniques are sometimes unnecessarily large, which can lead t...
Yi Zhang 0006, Samuel Burer, W. Nick Street
JMLR
2010
118views more  JMLR 2010»
14 years 6 months ago
On Over-fitting in Model Selection and Subsequent Selection Bias in Performance Evaluation
Model selection strategies for machine learning algorithms typically involve the numerical optimisation of an appropriate model selection criterion, often based on an estimator of...
Gavin C. Cawley, Nicola L. C. Talbot
82
Voted
ICML
2010
IEEE
15 years 27 days ago
Active Risk Estimation
We address the problem of evaluating the risk of a given model accurately at minimal labeling costs. This problem occurs in situations in which risk estimates cannot be obtained f...
Christoph Sawade, Niels Landwehr, Steffen Bickel, ...