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IJCAI
1989
15 years 8 months ago
An Empirical Comparison of Pattern Recognition, Neural Nets, and Machine Learning Classification Methods
Classification methods from statistical pattern recognition, neural nets, and machine learning were applied to four real-world data sets. Each of these data sets has been previous...
Sholom M. Weiss, Ioannis Kapouleas
ICASSP
2010
IEEE
15 years 7 months ago
Learning from high-dimensional noisy data via projections onto multi-dimensional ellipsoids
In this paper, we examine the problem of learning from noisecontaminated data in high-dimensional space. A new learning approach based on projections onto multi-dimensional ellips...
Liuling Gong, Dan Schonfeld
CE
2008
86views more  CE 2008»
15 years 7 months ago
Computer game design: Opportunities for successful learning
Developing children as successful learners is a key aim of A Curriculum for Excellence in Scotland. This paper presents qualitative results from an eight week exploratory field st...
Judy Robertson, Cathrin Howells
ML
1998
ACM
220views Machine Learning» more  ML 1998»
15 years 6 months ago
Learning to Improve Coordinated Actions in Cooperative Distributed Problem-Solving Environments
Abstract. Coordination is an essential technique in cooperative, distributed multiagent systems. However, sophisticated coordination strategies are not always cost-effective in all...
Toshiharu Sugawara, Victor R. Lesser
ML
1998
ACM
153views Machine Learning» more  ML 1998»
15 years 6 months ago
Bayesian Landmark Learning for Mobile Robot Localization
To operate successfully in indoor environments, mobile robots must be able to localize themselves. Most current localization algorithms lack flexibility, autonomy, and often optim...
Sebastian Thrun