ECML
2003
Springer
14 years 9 months ago
2003
Springer
Abstract. Classical learning algorithms from the fields of artificial neural networks and machine learning, typically, do not take any costs into account or allow only costs depe...
COLT
2003
Springer
14 years 9 months ago
2003
Springer
A general class of no-regret learning algorithms, called no-Φ-regret learning algorithms, is defined which spans the spectrum from no-external-regret learning to no-internal-reg...
MICAI
2004
Springer
14 years 9 months ago
2004
Springer
Abstract. Conventional artificial neural network models lack many physiological properties of the neuron. Current learning algorithms are more concerned to computational performanc...
ATAL
2004
Springer
14 years 9 months ago
2004
Springer
This paper investigates a relatively new direction in Multiagent Reinforcement Learning. Most multiagent learning techniques focus on Nash equilibria as elements of both the learn...
ICML
2004
IEEE
14 years 10 months ago
2004
IEEE
While there is a lot of empirical evidence showing that traditional rule learning approaches work well in practice, it is nearly impossible to derive analytical results about thei...
ISMIS
2005
Springer
14 years 10 months ago
2005
Springer
With the rapid advancement of information technology, scalability has become a necessity for learning algorithms to deal with large, real-world data repositories. In this paper, sc...
ICNC
2005
Springer
14 years 10 months ago
2005
Springer
Abstract. A mixture multiscale autoregressive moving average (ARMA) network is proposed for unsupervised segmentation of synthetic aperture radar (SAR) image. The network combines ...
ICDM
2005
IEEE
14 years 10 months ago
2005
IEEE
Active machine learning algorithms are used when large numbers of unlabeled examples are available and getting labels for them is costly (e.g. requiring consulting a human expert)...
IJCNN
2006
IEEE
14 years 10 months ago
2006
IEEE
— It is difficult to map many existing learning algorithms onto biological networks because the former require a separate learning network. The computational basis of biological...
ICANN
2007
Springer
14 years 10 months ago
2007
Springer
Finding the largest linearly separable set of examples for a given Boolean function is a NP-hard problem, that is relevant to neural network learning algorithms and to several prob...