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TNN
2008
106views more  TNN 2008»
15 years 4 months ago
Unsupervised Segmentation With Dynamical Units
In this paper, we present a novel network to separate mixtures of inputs that have been previously learned. A significant capability of the network is that it segments the componen...
A. Ravishankar Rao, Guillermo A. Cecchi, Charles C...
TROB
2008
86views more  TROB 2008»
15 years 4 months ago
Visual SLAM for Flying Vehicles
The ability to learn a map of the environment is important for numerous types of robotic vehicles. In this paper, we address the problem of learning a visual map of the ground usin...
Bastian Steder, Giorgio Grisetti, Cyrill Stachniss...
TVLSI
2008
140views more  TVLSI 2008»
15 years 4 months ago
A Novel Mutation-Based Validation Paradigm for High-Level Hardware Descriptions
We present a Mutation-based Validation Paradigm (MVP) technology that can handle complete high-level microprocessor implementations and is based on explicit design error modeling, ...
Jorge Campos, Hussain Al-Asaad
JAIR
1998
198views more  JAIR 1998»
15 years 4 months ago
Probabilistic Inference from Arbitrary Uncertainty using Mixtures of Factorized Generalized Gaussians
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
Alberto Ruiz, Pedro E. López-de-Teruel, M. ...
JMLR
2002
140views more  JMLR 2002»
15 years 4 months ago
On Boosting with Polynomially Bounded Distributions
We construct a framework which allows an algorithm to turn the distributions produced by some boosting algorithms into polynomially smooth distributions (w.r.t. the PAC oracle...
Nader H. Bshouty, Dmitry Gavinsky