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FLAIRS
1998
15 years 8 months ago
Decision Making in Qualitative Influence Diagrams
The increasing number of knowledge-based systems that build on a Bayesian belief network or influence diagram acknowledge the usefulness of these frameworks for addressing complex...
Silja Renooij, Linda C. van der Gaag
NSPW
2006
ACM
16 years 16 days ago
Sanitization models and their limitations
This work explores issues of computational disclosure control. We examine assumptions in the foundations of traditional problem statements and abstract models. We offer a comprehe...
Rick Crawford, Matt Bishop, Bhume Bhumiratana, Lis...
TON
2010
122views more  TON 2010»
15 years 5 months ago
The (in)completeness of the observed internet AS-level structure
— Despite significant efforts to obtain an accurate picture of the Internet’s connectivity structure at the level of individual autonomous systems (ASes), much has remained un...
Ricardo V. Oliveira, Dan Pei, Walter Willinger, Be...
JMLR
2010
192views more  JMLR 2010»
15 years 1 months ago
Efficient Learning of Deep Boltzmann Machines
We present a new approximate inference algorithm for Deep Boltzmann Machines (DBM's), a generative model with many layers of hidden variables. The algorithm learns a separate...
Ruslan Salakhutdinov, Hugo Larochelle
COLT
1999
Springer
15 years 11 months ago
Regret Bounds for Prediction Problems
We present a unified framework for reasoning about worst-case regret bounds for learning algorithms. This framework is based on the theory of duality of convex functions. It brin...
Geoffrey J. Gordon