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» Models for Incomplete and Probabilistic Information
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ICASSP
2008
IEEE
15 years 10 months ago
Automatic lecture transcription by exploiting presentation slide information for language model adaptation
The paper addresses language model adaptation for automatic lecture transcription by fully exploiting presentation slide information used in the lecture. As the text in the presen...
Tatsuya Kawahara, Yusuke Nemoto, Yuya Akita
ICPR
2004
IEEE
16 years 5 months ago
Model Based Object Recognition by Robust Information Fusion
Given a set of 3D model features and their 2D image, model based object recognition determines the correspondences between those features and hence computes the pose of the object...
Haifeng Chen, Ilan Shimshoni, Peter Meer
ICML
2000
IEEE
16 years 4 months ago
Maximum Entropy Markov Models for Information Extraction and Segmentation
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...
Andrew McCallum, Dayne Freitag, Fernando C. N. Per...
ICTIR
2009
Springer
15 years 10 months ago
Modeling Expected Utility of Multi-session Information Distillation
Abstract. An open challenge in information distillation is the evaluation and optimization of the utility of ranked lists with respect to flexible user interactions over multiple ...
Yiming Yang, Abhimanyu Lad
BMCBI
2006
112views more  BMCBI 2006»
15 years 4 months ago
Algorithms for incorporating prior topological information in HMMs: application to transmembrane proteins
Background: Hidden Markov Models (HMMs) have been extensively used in computational molecular biology, for modelling protein and nucleic acid sequences. In many applications, such...
Pantelis G. Bagos, Theodore D. Liakopoulos, Stavro...