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ML
2002
ACM
178views Machine Learning» more  ML 2002»
15 years 6 months ago
Metric-Based Methods for Adaptive Model Selection and Regularization
We present a general approach to model selection and regularization that exploits unlabeled data to adaptively control hypothesis complexity in supervised learning tasks. The idea ...
Dale Schuurmans, Finnegan Southey
TSP
2008
107views more  TSP 2008»
15 years 5 months ago
On Energy-Based Acoustic Source Localization for Sensor Networks
In this paper, energy-based localization methods for source localization in sensor networks are examined. The focus is on least-squares-based approaches due to a good tradeoff betw...
Chartchai Meesookho, Urbashi Mitra, Shrikanth Nara...
PR
2010
147views more  PR 2010»
15 years 4 months ago
Minimum classification error learning for sequential data in the wavelet domain
Wavelet analysis has found widespread use in signal processing and many classification tasks. Nevertheless, its use in dynamic pattern recognition have been much more restricted ...
D. Tomassi, Diego H. Milone, L. Forzani
SSPR
2010
Springer
15 years 4 months ago
Non-parametric Mixture Models for Clustering
Mixture models have been widely used for data clustering. However, commonly used mixture models are generally of a parametric form (e.g., mixture of Gaussian distributions or GMM),...
Pavan Kumar Mallapragada, Rong Jin, Anil K. Jain
ICCV
2009
IEEE
15 years 4 months ago
SCRAMSAC: Improving RANSAC's efficiency with a spatial consistency filter
Geometric verification with RANSAC has become a crucial step for many local feature based matching applications. Therefore, the details of its implementation are directly relevant...
Torsten Sattler, Bastian Leibe, Leif Kobbelt