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KDD
2008
ACM
137views Data Mining» more  KDD 2008»
16 years 4 months ago
Learning classifiers from only positive and unlabeled data
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
Charles Elkan, Keith Noto
131
Voted
HRI
2006
ACM
15 years 10 months ago
Using context and sensory data to learn first and second person pronouns
We present a method of grounded word learning that is powerful enough to learn the meanings of first and second person pronouns. The model uses the understood words in an utteran...
Kevin Gold, Brian Scassellati
SBIA
2004
Springer
15 years 9 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...
ATAL
2003
Springer
15 years 9 months ago
Natural methods for robot task learning: instructive demonstrations, generalization and practice
Among humans, teaching various tasks is a complex process which relies on multiple means for interaction and learning, both on the part of the teacher and of the learner. Used tog...
Monica N. Nicolescu, Maja J. Mataric
HICSS
2002
IEEE
153views Biometrics» more  HICSS 2002»
15 years 9 months ago
Technology Supported Learning Applied to an Innovative, Integrated Curriculum for First-Year Engineering Majors
In September of 1998, the College of Engineering at the University of Massachusetts Dartmouth piloted an innovative, integrated, first-year curriculum. It dramatically changed 31 ...
Paul J. Fortier, Emily Fowler, Raymond N. Laoulach...