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ICML
2009
IEEE
14 years 8 months ago
Importance weighted active learning
We propose an importance weighting framework for actively labeling samples. This technique yields practical yet sound active learning algorithms for general loss functions. Experi...
Alina Beygelzimer, Sanjoy Dasgupta, John Langford
JMLR
2010
82views more  JMLR 2010»
13 years 2 months ago
Negative Results for Active Learning with Convex Losses
We study the problem of active learning with convex loss functions. We prove that even under bounded noise constraints, the minimax rates for proper active learning are often no b...
Steve Hanneke, Liu Yang
ALT
2008
Springer
14 years 4 months ago
Active Learning of Group-Structured Environments
The question investigated in this paper is to what extent an input representation influences the success of learning, in particular from the point of view of analyzing agents that...
Gábor Bartók, Csaba Szepesvár...
CVPR
2012
IEEE
11 years 10 months ago
Two-person interaction detection using body-pose features and multiple instance learning
Human activity recognition has potential to impact a wide range of applications from surveillance to human computer interfaces to content based video retrieval. Recently, the rapi...
Kiwon Yun, Jean Honorio, Debaleena Chattopadhyay, ...
ICRA
2009
IEEE
125views Robotics» more  ICRA 2009»
14 years 2 months ago
Learning motor primitives for robotics
— The acquisition and self-improvement of novel motor skills is among the most important problems in robotics. Motor primitives offer one of the most promising frameworks for the...
Jens Kober, Jan Peters