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ICDAR
1999
IEEE
15 years 8 months ago
Cursive Character Detection using Incremental Learning
This paper describes a new hybrid architecture for an artificial neural network classifier that enables incremental learning. The learning algorithm of the proposed architecture d...
Jean-François Hébert, Marc Parizeau,...
EMMCVPR
1999
Springer
15 years 8 months ago
On Fitting Mixture Models
Consider the problem of tting a nite Gaussian mixture, with an unknown number of components, to observed data. This paper proposes a new minimum description length (MDL) type crite...
Mário A. T. Figueiredo, José M. N. L...
AIPS
2010
15 years 6 months ago
The Joy of Forgetting: Faster Anytime Search via Restarting
Anytime search algorithms solve optimisation problems by quickly finding a usually suboptimal solution and then finding improved solutions when given additional time. To deliver a...
Silvia Richter, Jordan Tyler Thayer, Wheeler Ruml
AAAI
2008
15 years 6 months ago
Efficient Learning of Action Schemas and Web-Service Descriptions
This work addresses the problem of efficiently learning action schemas using a bounded number of samples (interactions with the environment). We consider schemas in two languages-...
Thomas J. Walsh, Michael L. Littman
134
Voted
CG
2008
Springer
15 years 6 months ago
Whole-History Rating: A Bayesian Rating System for Players of Time-Varying Strength
Whole-History Rating (WHR) is a new method to estimate the time-varying strengths of players involved in paired comparisons. Like many variations of the Elo rating system, the whol...
Rémi Coulom