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» Learning Probabilistic Models of Relational Structure
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115
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ECCV
2002
Springer
16 years 2 months ago
Implicit Probabilistic Models of Human Motion for Synthesis and Tracking
Abstract. This paper addresses the problem of probabilistically modeling 3D human motion for synthesis and tracking. Given the high dimensional nature of human motion, learning an ...
Hedvig Sidenbladh, Michael J. Black, Leonid Sigal
103
Voted
EMNLP
2010
14 years 10 months ago
Confidence in Structured-Prediction Using Confidence-Weighted Models
Confidence-Weighted linear classifiers (CW) and its successors were shown to perform well on binary and multiclass NLP problems. In this paper we extend the CW approach for sequen...
Avihai Mejer, Koby Crammer
107
Voted
ICDE
2010
IEEE
224views Database» more  ICDE 2010»
16 years 7 days ago
Probabilistic Declarative Information Extraction
Abstract-Unstructured text represents a large fraction of the world's data. It often contain snippets of structured information within them (e.g., people's names and zip ...
Daisy Zhe Wang, Eirinaios Michelakis, Joseph M. He...
101
Voted
HRI
2006
ACM
15 years 6 months ago
Structural descriptions in human-assisted robot visual learning
The paper presents an approach to using structural descriptions, obtained through a human-robot tutoring dialogue, as labels for the visual object models a robot learns. The paper...
Geert-Jan M. Kruijff, John D. Kelleher, Gregor Ber...
BMCBI
2011
14 years 4 months ago
Learning sparse models for a dynamic Bayesian network classifier of protein secondary structure
Background: Protein secondary structure prediction provides insight into protein function and is a valuable preliminary step for predicting the 3D structure of a protein. Dynamic ...
Zafer Aydin, Ajit Singh, Jeff Bilmes, William Staf...