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» Evaluating learning algorithms and classifiers
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NIPS
2004
15 years 5 months ago
Convergence and No-Regret in Multiagent Learning
Learning in a multiagent system is a challenging problem due to two key factors. First, if other agents are simultaneously learning then the environment is no longer stationary, t...
Michael H. Bowling
GECCO
2006
Springer
195views Optimization» more  GECCO 2006»
15 years 8 months ago
Studying XCS/BOA learning in Boolean functions: structure encoding and random Boolean functions
Recently, studies with the XCS classifier system on Boolean functions have shown that in certain types of functions simple crossover operators can lead to disruption and, conseque...
Martin V. Butz, Martin Pelikan
MICCAI
2008
Springer
16 years 5 months ago
Classification of Suspected Liver Metastases Using fMRI Images: A Machine Learning Approach
Abstract. This paper presents a machine-learning approach to the interactive classification of suspected liver metastases in fMRI images. The method uses fMRI-based statistical mod...
Moti Freiman, Yifat Edrei, Yehonatan Sela, Yitz...
SIGIR
2008
ACM
15 years 4 months ago
Learning query intent from regularized click graphs
This work presents the use of click graphs in improving query intent classifiers, which are critical if vertical search and general-purpose search services are to be offered in a ...
Xiao Li, Ye-Yi Wang, Alex Acero
ICML
2006
IEEE
16 years 5 months ago
Multiclass boosting with repartitioning
A multiclass classification problem can be reduced to a collection of binary problems with the aid of a coding matrix. The quality of the final solution, which is an ensemble of b...
Ling Li