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ICML
2008
IEEE
16 years 7 months ago
No-regret learning in convex games
Quite a bit is known about minimizing different kinds of regret in experts problems, and how these regret types relate to types of equilibria in the multiagent setting of repeated...
Geoffrey J. Gordon, Amy R. Greenwald, Casey Marks
WWW
2009
ACM
16 years 7 months ago
Towards context-aware search by learning a very large variable length hidden markov model from search logs
Capturing the context of a user's query from the previous queries and clicks in the same session may help understand the user's information need. A context-aware approac...
Huanhuan Cao, Daxin Jiang, Jian Pei, Enhong Chen, ...
CVPR
2010
IEEE
16 years 2 months ago
Efficient Piecewise Learning for Conditional Random Fields
Conditional Random Field models have proved effective for several low-level computer vision problems. Inference in these models involves solving a combinatorial optimization probl...
Karteek Alahari, Phil Torr
TEI
2010
ACM
201views Hardware» more  TEI 2010»
16 years 1 months ago
Objects in play: virtual environments and tactile learning
When creating technology environments for children, consideration needs to be given to how touch, gesture, and physical interactions impact on play and learning. This is particula...
Lillian Spina-Caza
IROS
2008
IEEE
111views Robotics» more  IROS 2008»
16 years 1 months ago
Learning perceptual coupling for motor primitives
—Dynamic system-based motor primitives [1] have enabled robots to learn complex tasks ranging from Tennisswings to locomotion. However, to date there have been only few extension...
Jens Kober, Betty J. Mohler, Jan Peters