Learning conditional structures in graphical models from a large set of observation streams through efficient discretisation

Carl Henrik Ek, Dan Song, Danica Kragic

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

Original language	English
Title of host publication	IEEE International Conference on Robotics and Automation, Workshop on Manipulation under Uncertainty
Pages	1-5
Number of pages	5
Publication status	Published - 2011

Handle.net

@inproceedings{7a3f2397596a48fba37e7832be91117f,

title = "Learning conditional structures in graphical models from a large set of observation streams through efficient discretisation",

author = "Ek, {Carl Henrik} and Dan Song and Danica Kragic",

year = "2011",

language = "English",

pages = "1--5",

booktitle = "IEEE International Conference on Robotics and Automation, Workshop on Manipulation under Uncertainty",

}

Learning conditional structures in graphical models from a large set of observation streams through efficient discretisation. / Ek, Carl Henrik; Song, Dan; Kragic, Danica.
IEEE International Conference on Robotics and Automation, Workshop on Manipulation under Uncertainty. 2011. p. 1-5.

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

TY - GEN

T1 - Learning conditional structures in graphical models from a large set of observation streams through efficient discretisation

AU - Ek, Carl Henrik

AU - Song, Dan

AU - Kragic, Danica

PY - 2011

Y1 - 2011

M3 - Conference Contribution (Conference Proceeding)

SP - 1

EP - 5

BT - IEEE International Conference on Robotics and Automation, Workshop on Manipulation under Uncertainty

ER -