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» Using Machine Learning to Focus Iterative Optimization
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PLDI
2011
ACM
14 years 5 months ago
Isolating and understanding concurrency errors using reconstructed execution fragments
In this paper we propose Recon, a new general approach to concurrency debugging. Recon goes beyond just detecting bugs, it also presents to the programmer short fragments of buggy...
Brandon Lucia, Benjamin P. Wood, Luis Ceze
KDD
2006
ACM
149views Data Mining» more  KDD 2006»
16 years 2 months ago
Regularized discriminant analysis for high dimensional, low sample size data
Linear and Quadratic Discriminant Analysis have been used widely in many areas of data mining, machine learning, and bioinformatics. Friedman proposed a compromise between Linear ...
Jieping Ye, Tie Wang
GECCO
2006
Springer
171views Optimization» more  GECCO 2006»
15 years 6 months ago
Evolving ensemble of classifiers in random subspace
Various methods for ensemble selection and classifier combination have been designed to optimize the results of ensembles of classifiers. Genetic algorithm (GA) which uses the div...
Albert Hung-Ren Ko, Robert Sabourin, Alceu de Souz...
CORR
2010
Springer
136views Education» more  CORR 2010»
14 years 12 months ago
An Inverse Power Method for Nonlinear Eigenproblems with Applications in 1-Spectral Clustering and Sparse PCA
Many problems in machine learning and statistics can be formulated as (generalized) eigenproblems. In terms of the associated optimization problem, computing linear eigenvectors a...
Matthias Hein, Thomas Bühler
121
Voted
CHI
2008
ACM
16 years 2 months ago
Activity sensing in the wild: a field trial of ubifit garden
Recent advances in small inexpensive sensors, low-power processing, and activity modeling have enabled applications that use on-body sensing and machine learning to infer people&#...
Sunny Consolvo, David W. McDonald, Tammy Toscos, M...