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» The Complexity of Belief Update
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ICML
2008
IEEE
16 years 7 months ago
On the quantitative analysis of deep belief networks
Deep Belief Networks (DBN's) are generative models that contain many layers of hidden variables. Efficient greedy algorithms for learning and approximate inference have allow...
Ruslan Salakhutdinov, Iain Murray
WCNC
2008
IEEE
16 years 16 days ago
Decoding on Graphs: LDPC-Coded MISO Systems and Belief Propagation
— This paper proposes a new approach for decoding LDPC codes over MISO channels. Since in an nT × 1 MISO system with a modulation of alphabet size 2M, nT transmitted symbols are...
Amir H. Djahanshahi, Paul H. Siegel, Laurence B. M...
ECML
2003
Springer
15 years 11 months ago
Robust k-DNF Learning via Inductive Belief Merging
A central issue in logical concept induction is the prospect of inconsistency. This problem may arise due to noise in the training data, or because the target concept does not fit...
Frédéric Koriche, Joël Quinquet...
NOMS
2002
IEEE
130views Communications» more  NOMS 2002»
15 years 11 months ago
End-to-end service failure diagnosis using belief networks
We present fault localization techniques suitable for diagnosing end-to-end service problems in communication systems with complex topologies. We refine a layered system model th...
Malgorzata Steinder, Adarshpal S. Sethi
AAAI
2008
15 years 8 months ago
Lifted First-Order Belief Propagation
Unifying first-order logic and probability is a long-standing goal of AI, and in recent years many representations combining aspects of the two have been proposed. However, infere...
Parag Singla, Pedro Domingos