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» Introduction to Randomized Algorithms
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MICCAI
2004
Springer
16 years 4 months ago
3D Bayesian Regularization of Diffusion Tensor MRI Using Multivariate Gaussian Markov Random Fields
3D Bayesian regularization applied to diffusion tensor MRI is presented here. The approach uses Markov Random Field ideas and is based upon the definition of a 3D neighborhood syst...
Marcos Martín-Fernández, Carl-Fredri...
ICML
2007
IEEE
16 years 4 months ago
Conditional random fields for multi-agent reinforcement learning
Conditional random fields (CRFs) are graphical models for modeling the probability of labels given the observations. They have traditionally been trained with using a set of obser...
Xinhua Zhang, Douglas Aberdeen, S. V. N. Vishwanat...
ICML
2004
IEEE
16 years 4 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...
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SIGSOFT
2007
ACM
16 years 4 months ago
Recommending random walks
We improve on previous recommender systems by taking advantage of the layered structure of software. We use a random-walk approach, mimicking the more focused behavior of a develo...
Zachary M. Saul, Vladimir Filkov, Premkumar T. Dev...
SIGMOD
2009
ACM
189views Database» more  SIGMOD 2009»
16 years 3 months ago
Query segmentation using conditional random fields
A growing mount of available text data are being stored in relational databases, giving rise to an increasing need for the RDBMSs to support effective text retrieval. In this pape...
Xiaohui Yu, Huxia Shi