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ML
1998
ACM
153views Machine Learning» more  ML 1998»
15 years 2 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
132
Voted
AGENTS
1999
Springer
15 years 6 months ago
A Personal News Agent That Talks, Learns and Explains
Most work on intelligent information agents has thus far focused on systems that are accessible through the World Wide Web. As demanding schedules prohibit people from continuous ...
Daniel Billsus, Michael J. Pazzani
115
Voted
FLAIRS
2007
15 years 4 months ago
A Distance-Based Over-Sampling Method for Learning from Imbalanced Data Sets
Many real-world domains present the problem of imbalanced data sets, where examples of one classes significantly outnumber examples of other classes. This makes learning difficu...
Jorge de la Calleja, Olac Fuentes
137
Voted
INTEGRATION
2010
172views more  INTEGRATION 2010»
15 years 1 months ago
Analog circuits optimization based on evolutionary computation techniques
1 — This paper presents a new design automation tool based on a modified genetic algorithm kernel, in order to increase efficiency on the analog circuit and system design cycle. ...
Manuel F. M. Barros, Jorge Guilherme, Nuno Horta
168
Voted
ALT
2009
Springer
15 years 11 months ago
Average-Case Active Learning with Costs
Abstract. We analyze the expected cost of a greedy active learning algorithm. Our analysis extends previous work to a more general setting in which different queries have differe...
Andrew Guillory, Jeff A. Bilmes