111 search results - page 11 / 23 » Perspectives on Sparse Bayesian Learning |
ICIP
2008
IEEE
16 years 1 months ago
2008
IEEE
This paper introduces a novel way to leverage the implicit geometry of sparse local features (e.g. SIFT operator) for the purposes of object detection and segmentation. A two-clas...
JMLR
2002
14 years 11 months ago
2002
Approximate Bayesian Gaussian process (GP) classification techniques are powerful nonparametric learning methods, similar in appearance and performance to support vector machines....
CORR
2011
Springer
2011
Springer
Iterative Reweighted Algorithms for Sparse Signal Recovery with Temporally Correlated Source Vectors
14 years 6 months ago
Iterative reweighted algorithms, as a class of algorithms for sparse signal recovery, have been found to have better performance than their non-reweighted counterparts. However, f...
ICPR
2010
IEEE
14 years 9 months ago
2010
IEEE
In this paper we redefine and generalize the classic k-nearest neighbors (k-NN) voting rule in a Bayesian maximum-a-posteriori (MAP) framework. Therefore, annotated examples are u...
IJCAI
2007
15 years 1 months ago
2007
A key problem in reinforcement learning is finding a good balance between the need to explore the environment and the need to gain rewards by exploiting existing knowledge. Much ...