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» Learning for Sequence Extraction Tasks
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ECML
2007
Springer
14 years 4 months ago
Separating Precision and Mean in Dirichlet-Enhanced High-Order Markov Models
Abstract. Robustly estimating the state-transition probabilities of highorder Markov processes is an essential task in many applications such as natural language modeling or protei...
Rikiya Takahashi
ICDM
2005
IEEE
148views Data Mining» more  ICDM 2005»
14 years 3 months ago
Hot Item Mining and Summarization from Multiple Auction Web Sites
Online auction Web sites are fast changing, highly dynamic, and complex as they involve tremendous sellers and potential buyers, as well as a huge amount of items listed for biddi...
Tak-Lam Wong, Wai Lam
ICANN
2005
Springer
14 years 3 months ago
Learning Features of Intermediate Complexity for the Recognition of Biological Motion
Humans can recognize biological motion from strongly impoverished stimuli, like point-light displays. Although the neural mechanism underlying this robust perceptual process have n...
Rodrigo Sigala, Thomas Serre, Tomaso Poggio, Marti...
FGR
2008
IEEE
208views Biometrics» more  FGR 2008»
14 years 4 months ago
Unsupervised learning from local features for video-based face recognition
This paper presents an unsupervised learning approach to video-based face recognition that does not make any assumptions about the pose, expressions or prior localization of landm...
Ajmal Mian
ICMCS
2009
IEEE
130views Multimedia» more  ICMCS 2009»
13 years 7 months ago
Fast multi-reference motion estimation via statistical learning for H.264/AVC
In the H.264/AVC coding standard, motion estimation (ME) is allowed to use multiple reference frames to make full use of reducing temporal redundancy in a video sequence. Although...
Chen-Kuo Chiang, Shang-Hong Lai