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ICML
2000
IEEE
15 years 10 months ago
Solving the Multiple-Instance Problem: A Lazy Learning Approach
As opposed to traditional supervised learning, multiple-instance learning concerns the problem of classifying a bag of instances, given bags that are labeled by a teacher as being...
Jun Wang, Jean-Daniel Zucker
ALT
2010
Springer
14 years 11 months ago
Online Multiple Kernel Learning: Algorithms and Mistake Bounds
Online learning and kernel learning are two active research topics in machine learning. Although each of them has been studied extensively, there is a limited effort in addressing ...
Rong Jin, Steven C. H. Hoi, Tianbao Yang
88
Voted
ICML
2005
IEEE
15 years 10 months ago
Learning Gaussian processes from multiple tasks
We consider the problem of multi-task learning, that is, learning multiple related functions. Our approach is based on a hierarchical Bayesian framework, that exploits the equival...
Kai Yu, Volker Tresp, Anton Schwaighofer
78
Voted
ICRA
2009
IEEE
179views Robotics» more  ICRA 2009»
15 years 4 months ago
Automatic weight learning for multiple data sources when learning from demonstration
— Traditional approaches to programming robots are generally inaccessible to non-robotics-experts. A promising exception is the Learning from Demonstration paradigm. Here a polic...
Brenna Argall, Brett Browning, Manuela M. Veloso
72
Voted
ICML
2008
IEEE
15 years 10 months ago
Bayesian multiple instance learning: automatic feature selection and inductive transfer
Vikas C. Raykar, Balaji Krishnapuram, Jinbo Bi, Mu...