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ECCV
2006
Springer
16 years 14 days ago
Efficient Belief Propagation with Learned Higher-Order Markov Random Fields
Belief propagation (BP) has become widely used for low-level vision problems and various inference techniques have been proposed for loopy graphs. These methods typically rely on a...
Xiangyang Lan, Stefan Roth, Daniel P. Huttenlocher...
MLG
2007
Springer
15 years 4 months ago
A Universal Kernel for Learning Regular Languages
We give a universal kernel that renders all the regular languages linearly separable. We are not able to compute this kernel efficiently and conjecture that it is intractable, but...
Leonid Kontorovich
SCHULE
2007
Springer
15 years 4 months ago
Exploratory Learning
: In our department we have a long history of developing interfaces for learning, which are framed by constructivist and constructionist theories of learning. Thus we try to create...
Ivan Kalas, D. Lehotska
AUSAI
2003
Springer
15 years 3 months ago
Choosing Learning Algorithms Using Sign Tests with High Replicability
An important task in machine learning is determining which learning algorithm works best for a given data set. When the amount of data is small the same data needs to be used repea...
Remco R. Bouckaert
ATAL
2010
Springer
14 years 11 months ago
Evolving policy geometry for scalable multiagent learning
A major challenge for traditional approaches to multiagent learning is to train teams that easily scale to include additional agents. The problem is that such approaches typically...
David B. D'Ambrosio, Joel Lehman, Sebastian Risi, ...