60 search results - page 3 / 12 » Bayesian Inference and Optimal Design for the Sparse Linear ... |
NIPS
2007
13 years 6 months ago
2007
Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the ...
ICA
2007
Springer
13 years 8 months ago
2007
Springer
Abstract. A nonparametric Bayesian extension of Independent Components Analysis (ICA) is proposed where observed data Y is modelled as a linear superposition, G, of a potentially i...
NIPS
2008
13 years 6 months ago
2008
Uncertainty is omnipresent when we perceive or interact with our environment, and the Bayesian framework provides computational methods for dealing with it. Mathematical models fo...
ICIP
2008
IEEE
14 years 6 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...
IJCAI
2007
13 years 6 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 ...