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ICML
2005
IEEE
16 years 5 months ago
Healing the relevance vector machine through augmentation
The Relevance Vector Machine (RVM) is a sparse approximate Bayesian kernel method. It provides full predictive distributions for test cases. However, the predictive uncertainties ...
Carl Edward Rasmussen, Joaquin Quiñonero Ca...
ICA
2004
Springer
15 years 9 months ago
On the Strong Uniqueness of Highly Sparse Representations from Redundant Dictionaries
A series of recent results shows that if a signal admits a sufficiently sparse representation (in terms of the number of nonzero coefficients) in an “incoherent” dictionary, th...
Rémi Gribonval, Morten Nielsen
ICML
2003
IEEE
16 years 5 months ago
The Cross Entropy Method for Fast Policy Search
We present a learning framework for Markovian decision processes that is based on optimization in the policy space. Instead of using relatively slow gradient-based optimization al...
Shie Mannor, Reuven Y. Rubinstein, Yohai Gat
BMCV
2000
Springer
15 years 8 months ago
Unsupervised Learning of Biologically Plausible Object Recognition Strategies
Recent psychological and neurological evidence suggests that biological object recognition is a process of matching sensed images to stored iconic memories. This paper presents a p...
Bruce A. Draper, Kyungim Baek
ICASSP
2010
IEEE
15 years 4 months ago
Empirical quantization for sparse sampling systems
We propose a quantization design technique (estimator) suitable for new compressed sensing sampling systems whose ultimate goal is classification or detection. The design is base...
Michael A. Lexa