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» Learning and using relational theories
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ICALP
2011
Springer
14 years 10 months ago
New Algorithms for Learning in Presence of Errors
We give new algorithms for a variety of randomly-generated instances of computational problems using a linearization technique that reduces to solving a system of linear equations...
Sanjeev Arora, Rong Ge
ICRA
2005
IEEE
146views Robotics» more  ICRA 2005»
16 years 10 days ago
Probabilistic Gaze Imitation and Saliency Learning in a Robotic Head
— Imitation is a powerful mechanism for transferring knowledge from an instructor to a na¨ıve observer, one that is deeply contingent on a state of shared attention between the...
Aaron P. Shon, David B. Grimes, Chris Baker, Matth...
CORR
2012
Springer
170views Education» more  CORR 2012»
14 years 2 months ago
What Cannot be Learned with Bethe Approximations
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its B...
Uri Heinemann, Amir Globerson
ISBI
2002
IEEE
16 years 7 months ago
Learning multispectral texture features for cervical cancer detection
We present a bottom-up approach for automatic cancer cell detection in multispectral microscopic thin Pap smear images. Around 4,000 multispectral texture features are explored fo...
Yanxi Liu, Tong Zhao, Jiayong Zhang
ICRA
2003
IEEE
116views Robotics» more  ICRA 2003»
16 years 1 days ago
Learning to role-switch in multi-robot systems
We present an approach that uses Q-learning on individual robotic agents, for coordinating a missiontasked team of robots in a complex scenario. To reduce the size of the state sp...
Eric Martinson, Ronald C. Arkin