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ML
2002
ACM
178views Machine Learning» more  ML 2002»
15 years 5 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
ML
2010
ACM
141views Machine Learning» more  ML 2010»
15 years 4 months ago
Relational retrieval using a combination of path-constrained random walks
Scientific literature with rich metadata can be represented as a labeled directed graph. This graph representation enables a number of scientific tasks such as ad hoc retrieval o...
Ni Lao, William W. Cohen
DATAMINE
2010
161views more  DATAMINE 2010»
15 years 3 months ago
Predicting labels for dyadic data
: In dyadic prediction, the input consists of a pair of items (a dyad), and the goal is to predict the value of an observation related to the dyad. Special cases of dyadic predicti...
Aditya Krishna Menon, Charles Elkan
UAI
2008
15 years 7 months ago
Dyna-Style Planning with Linear Function Approximation and Prioritized Sweeping
We consider the problem of efficiently learning optimal control policies and value functions over large state spaces in an online setting in which estimates must be available afte...
Richard S. Sutton, Csaba Szepesvári, Alborz...
ICIP
2008
IEEE
16 years 7 months ago
Supervised methods for perfect segmentation in medical images
We pose the problem of perfect segmentation for regions with ambiguous boundaries. We design machine learning classifiers to identify boundaries and build these into an interactiv...
Tony Shepherd, Daniel C. Alexander