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ICML
2004
IEEE
14 years 5 months ago
Learning random walk models for inducing word dependency distributions
Many NLP tasks rely on accurately estimating word dependency probabilities P(w1|w2), where the words w1 and w2 have a particular relationship (such as verb-object). Because of the...
Kristina Toutanova, Christopher D. Manning, Andrew...
ICCV
2009
IEEE
1048views Computer Vision» more  ICCV 2009»
14 years 9 months ago
Face Recognition With Contiguous Occlusion Using Markov Random Fields
Partially occluded faces are common in many applications of face recognition. While algorithms based on sparse representation have demonstrated promising results, they achieve t...
Zihan Zhou, Andrew Wagner, Hossein Mobahi, John Wr...
FOCS
2008
IEEE
13 years 11 months ago
Noise Tolerance of Expanders and Sublinear Expander Reconstruction
We consider the problem of online sublinear expander reconstruction and its relation to random walks in “noisy” expanders. Given access to an adjacency list representation of ...
Satyen Kale, Yuval Peres, C. Seshadhri
AAAI
2008
13 years 7 months ago
Hybrid Markov Logic Networks
Markov logic networks (MLNs) combine first-order logic and Markov networks, allowing us to handle the complexity and uncertainty of real-world problems in a single consistent fram...
Jue Wang, Pedro Domingos
ICML
2006
IEEE
14 years 5 months ago
A new approach to data driven clustering
We consider the problem of clustering in its most basic form where only a local metric on the data space is given. No parametric statistical model is assumed, and the number of cl...
Arik Azran, Zoubin Ghahramani