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116
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NIPS
1998
15 years 5 months ago
Lazy Learning Meets the Recursive Least Squares Algorithm
Lazy learning is a memory-based technique that, once a query is received, extracts a prediction interpolating locally the neighboring examples of the query which are considered re...
Mauro Birattari, Gianluca Bontempi, Hugues Bersini
115
Voted
ICCV
2005
IEEE
16 years 5 months ago
Learning Non-Negative Sparse Image Codes by Convex Programming
Example-based learning of codes that statistically encode general image classes is of vital importance for computational vision. Recently, non-negative matrix factorization (NMF) ...
Christoph Schnörr, Matthias Heiler
149
Voted
ICIP
2006
IEEE
16 years 5 months ago
Image Retrieval using Long-Term Semantic Learning
The automatic computation of features for content-based image retrieval still has difficulties to represent the concepts the user has in mind. Whenever an additional learning stra...
Matthieu Cord, Philippe Henri Gosselin
122
Voted
ICML
2007
IEEE
16 years 4 months ago
On one method of non-diagonal regularization in sparse Bayesian learning
In the paper we propose a new type of regularization procedure for training sparse Bayesian methods for classification. Transforming Hessian matrix of log-likelihood function to d...
Dmitry Kropotov, Dmitry Vetrov
165
Voted
WILF
2005
Springer
194views Fuzzy Logic» more  WILF 2005»
15 years 9 months ago
Learning Bayesian Classifiers from Gene-Expression MicroArray Data
Computing methods that allow the efficient and accurate processing of experimentally gathered data play a crucial role in biological research. The aim of this paper is to present a...
Andrea Bosin, Nicoletta Dessì, Diego Libera...