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CORR
2000
Springer
126views Education» more  CORR 2000»
13 years 8 months ago
Learning to Filter Spam E-Mail: A Comparison of a Naive Bayesian and a Memory-Based Approach
We investigate the performance of two machine learning algorithms in the context of antispam filtering. The increasing volume of unsolicited bulk e-mail (spam) has generated a nee...
Ion Androutsopoulos, Georgios Paliouras, Vangelis ...
ISBI
2006
IEEE
14 years 9 months ago
Assessing the accuracy of non-rigid registration with and without ground truth
We compare two methods for assessing the performance of groupwise non-rigid registration algorithms. One approach, which has been described previously, utilizes a measure of overl...
Roy Schestowitz, Carole J. Twining, Timothy F. Coo...
GECCO
2010
Springer
168views Optimization» more  GECCO 2010»
14 years 1 months ago
Investigating whether hyperNEAT produces modular neural networks
HyperNEAT represents a class of neuroevolutionary algorithms that captures some of the power of natural development with a ionally efficient high-level abstraction of development....
Jeff Clune, Benjamin E. Beckmann, Philip K. McKinl...
SBIA
2004
Springer
14 years 2 months ago
Learning with Drift Detection
Abstract. Most of the work in machine learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem...
João Gama, Pedro Medas, Gladys Castillo, Pe...
JMLR
2008
129views more  JMLR 2008»
13 years 8 months ago
Finite-Time Bounds for Fitted Value Iteration
In this paper we develop a theoretical analysis of the performance of sampling-based fitted value iteration (FVI) to solve infinite state-space, discounted-reward Markovian decisi...
Rémi Munos, Csaba Szepesvári