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FUZZIEEE
2007
IEEE
15 years 10 months ago
Learning Undirected Possibilistic Networks with Conditional Independence Tests
—Approaches based on conditional independence tests are among the most popular methods for learning graphical models from data. Due to the predominance of Bayesian networks in th...
Christian Borgelt
102
Voted
IROS
2007
IEEE
95views Robotics» more  IROS 2007»
15 years 10 months ago
Load estimation and control using learned dynamics models
— Classic adaptive control methods for handling varying loads rely on an analytically derived model of the robot’s dynamics. However, in many situations, it is not feasible or ...
Georgios Petkos, Sethu Vijayakumar
155
Voted
ICML
2010
IEEE
15 years 4 months ago
Sequential Projection Learning for Hashing with Compact Codes
Hashing based Approximate Nearest Neighbor (ANN) search has attracted much attention due to its fast query time and drastically reduced storage. However, most of the hashing metho...
Jun Wang, Sanjiv Kumar, Shih-Fu Chang
128
Voted
ICONIP
2010
15 years 2 months ago
Learning Basis Representations of Inverse Dynamics Models for Real-Time Adaptive Control
Abstract. In this paper, we propose a novel approach for adaptive control of robotic manipulators. Our approach uses a representation of inverse dynamics models learned from a vari...
Yasuhito Horiguchi, Takamitsu Matsubara, Masatsugu...
130
Voted
RECOMB
2010
Springer
15 years 5 months ago
Leveraging Sequence Classification by Taxonomy-Based Multitask Learning
In this work we consider an inference task that biologists are very good at: deciphering biological processes by bringing together knowledge that has been obtained by experiments u...
Christian Widmer, Jose Leiva, Yasemin Altun, Gunna...