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ECCV
1994
Springer
15 years 10 months ago
Markov Random Field Models in Computer Vision
A variety of computer vision problems can be optimally posed as Bayesian labeling in which the solution of a problem is dened as the maximum a posteriori (MAP) probability estimate...
Stan Z. Li
IADIS
2008
15 years 7 months ago
E-Learning In The Field Of E-Business Support
E-business is one important element promoting business competitiveness and is thus closely linked to innovation. However, the potentials of ICT for business processes are not yet ...
Elisabeth Mendoza
ACL
2004
15 years 7 months ago
Using Conditional Random Fields to Predict Pitch Accents in Conversational Speech
The detection of prosodic characteristics is an important aspect of both speech synthesis and speech recognition. Correct placement of pitch accents aids in more natural sounding ...
Michelle L. Gregory, Yasemin Altun
ACL
2006
15 years 7 months ago
Training Conditional Random Fields with Multivariate Evaluation Measures
This paper proposes a framework for training Conditional Random Fields (CRFs) to optimize multivariate evaluation measures, including non-linear measures such as F-score. Our prop...
Jun Suzuki, Erik McDermott, Hideki Isozaki
UAI
2004
15 years 7 months ago
Graph Partition Strategies for Generalized Mean Field Inference
An autonomous variational inference algorithm for arbitrary graphical models requires the ability to optimize variational approximations over the space of model parameters as well...
Eric P. Xing, Michael I. Jordan