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» A Framework for Multiple-Instance Learning
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ECIR
2010
Springer
15 years 6 months ago
Learning to Select a Ranking Function
Abstract. Learning To Rank (LTR) techniques aim to learn an effective document ranking function by combining several document features. While the function learned may be uniformly ...
Jie Peng, Craig Macdonald, Iadh Ounis
142
Voted
IJCAI
2007
15 years 6 months ago
Learning to Walk through Imitation
Programming a humanoid robot to walk is a challenging problem in robotics. Traditional approaches rely heavily on prior knowledge of the robot's physical parameters to devise...
Rawichote Chalodhorn, David B. Grimes, Keith Groch...
ICRA
2010
IEEE
158views Robotics» more  ICRA 2010»
15 years 3 months ago
Movement templates for learning of hitting and batting
Abstract— Hitting and batting tasks, such as tennis forehands, ping-pong strokes, or baseball batting, depend on predictions where the ball can be intercepted and how it can prop...
Jens Kober, Katharina Mülling, Oliver Kroemer...
CORR
2011
Springer
178views Education» more  CORR 2011»
14 years 8 months ago
Online Learning: Stochastic and Constrained Adversaries
Learning theory has largely focused on two main learning scenarios. The first is the classical statistical setting where instances are drawn i.i.d. from a fixed distribution and...
Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
MOBIHOC
2012
ACM
13 years 7 months ago
Spatial spectrum access game: nash equilibria and distributed learning
A key feature of wireless communications is the spatial reuse. However, the spatial aspect is not yet well understood for the purpose of designing efficient spectrum sharing mecha...
Xu Chen, Jianwei Huang