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» A New Discriminative Kernel From Probabilistic Models
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AAAI
2008
15 years 2 months ago
Structure Learning on Large Scale Common Sense Statistical Models of Human State
Research has shown promise in the design of large scale common sense probabilistic models to infer human state from environmental sensor data. These models have made use of mined ...
William Pentney, Matthai Philipose, Jeff A. Bilmes
ICDAR
2009
IEEE
15 years 6 months ago
Enhanced Text Extraction from Arabic Degraded Document Images Using EM Algorithm
This paper presents a new enhanced text extraction algorithm from degraded document images on the basis of the probabilistic models. The observed document image is considered as a...
Wafa Boussellaa, Aymen Bougacha, Abderrazak Zahour...
WWW
2004
ACM
16 years 15 days ago
Mining models of human activities from the web
The ability to determine what day-to-day activity (such as cooking pasta, taking a pill, or watching a video) a person is performing is of interest in many application domains. A ...
Mike Perkowitz, Matthai Philipose, Kenneth P. Fish...
BMCBI
2006
160views more  BMCBI 2006»
14 years 12 months ago
Gene prediction in eukaryotes with a generalized hidden Markov model that uses hints from external sources
Background: In order to improve gene prediction, extrinsic evidence on the gene structure can be collected from various sources of information such as genome-genome comparisons an...
Mario Stanke, Oliver Schöffmann, Burkhard Mor...
EMNLP
2008
15 years 1 months ago
Modeling Annotators: A Generative Approach to Learning from Annotator Rationales
A human annotator can provide hints to a machine learner by highlighting contextual "rationales" for each of his or her annotations (Zaidan et al., 2007). How can one ex...
Omar Zaidan, Jason Eisner