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» Using Random Forests in the Structured Language Model
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ICMLA
2008
13 years 10 months ago
Comprehensible Models for Predicting Molecular Interaction with Heart-Regulating Genes
When using machine learning for in silico modeling, the goal is normally to obtain highly accurate predictive models. Often, however, models should also bring insights into intere...
Cecilia Sönströd, Ulf Johansson, Ulf Nor...
ECCC
2007
62views more  ECCC 2007»
13 years 8 months ago
Space Hierarchy Results for Randomized and Other Semantic Models
We prove space hierarchy and separation results for randomized and other semantic models of computation with advice where a machine is only required to behave appropriately when g...
Jeff Kinne, Dieter van Melkebeek
CIKM
2008
Springer
13 years 10 months ago
Closing the loop in webpage understanding
The two most important tasks in information extraction from the Web are webpage structure understanding and natural language sentences processing. However, little work has been don...
Chunyu Yang, Yong Cao, Zaiqing Nie, Jie Zhou, Ji-R...
SCM
1998
13 years 10 months ago
Coordinated Editing of Versioned Packages in the JP Programming Environment
As part of an investigation of scalable development techniques for systems written in the JavaTM programming language, the Forest Project is building JP, a prototype distributed pr...
Michael L. Van de Vanter
ICDCS
1995
IEEE
14 years 5 days ago
A Distributed K-Mutual Exclusion Algorithm
This paper presents a token-based K-mutual exchsion algorithm. The algorithm uses K tokens and a dynamic forest structure for each token. This structure is used to forward token r...
Shailaja Bulgannawar, Nitin H. Vaidya