4930 search results - page 203 / 986 » Learning minimal abstractions |
166
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TKDE
2010
15 years 5 months ago
2010
—Local classifiers are sometimes called lazy learners because they do not train a classifier until presented with a test sample. However, such methods are generally not complet...
201
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JMLR
2010
15 years 1 months ago
2010
We use convex relaxation techniques to provide a sequence of regularized low-rank solutions for large-scale matrix completion problems. Using the nuclear norm as a regularizer, we...
226
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JMLR
2012
13 years 9 months ago
2012
The expectation maximization (EM) algorithm is a popular algorithm for parameter estimation in models with hidden variables. However, the algorithm has several non-trivial limitat...
181
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COLT
1999
Springer
15 years 11 months ago
1999
Springer
We present a unified framework for reasoning about worst-case regret bounds for learning algorithms. This framework is based on the theory of duality of convex functions. It brin...
171
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CORR
2008
Springer
15 years 6 months ago
2008
Springer
We prove existence and uniqueness of the minimizer for the average geodesic distance to the points of a geodesically convex set on the sphere. This implies a corresponding existen...