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» Scales and Scale-like Structures
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ICML
2007
IEEE
16 years 7 months ago
Piecewise pseudolikelihood for efficient training of conditional random fields
Discriminative training of graphical models can be expensive if the variables have large cardinality, even if the graphical structure is tractable. In such cases, pseudolikelihood...
Charles A. Sutton, Andrew McCallum
ICML
2005
IEEE
16 years 7 months ago
Harmonic mixtures: combining mixture models and graph-based methods for inductive and scalable semi-supervised learning
Graph-based methods for semi-supervised learning have recently been shown to be promising for combining labeled and unlabeled data in classification problems. However, inference f...
Xiaojin Zhu, John D. Lafferty
ICML
2003
IEEE
16 years 7 months ago
Principled Methods for Advising Reinforcement Learning Agents
An important issue in reinforcement learning is how to incorporate expert knowledge in a principled manner, especially as we scale up to real-world tasks. In this paper, we presen...
Eric Wiewiora, Garrison W. Cottrell, Charles Elkan
ICSE
2008
IEEE-ACM
16 years 7 months ago
Tool support for the navigation in graphical models
Graphical models are omnipresent in the software engineering field, but most current graphical modeling languages do not scale with the increasing size and complexity of today...
Tobias Reinhard, Silvio Meier, Reinhard Stoiber, C...
SIGSOFT
2006
ACM
16 years 7 months ago
How is aliasing used in systems software?
We present a study of all sources of aliasing in over one million lines of C code, identifying in the process the common patterns of aliasing that arise in practice. We find that ...
Brian Hackett, Alex Aiken