Stochastic regularization: Smoothness or similarity?
نویسندگان
چکیده
منابع مشابه
Adaptive Regularization for Similarity Measures
Algorithms for learning distributions over weight-vectors, such as AROW (Crammer et al., 2009) were recently shown empirically to achieve state-of-the-art performance at various problems, with strong theoretical guaranties. Extending these algorithms to matrix models pose challenges since the number of free parameters in the covariance of the distribution scales as n with the dimension n of the...
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ژورنال
عنوان ژورنال: Geophysical Research Letters
سال: 1998
ISSN: 0094-8276
DOI: 10.1029/98gl02183