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» A Framework for Multiple-Instance Learning
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KDD
2003
ACM
214views Data Mining» more  KDD 2003»
16 years 6 months ago
Adaptive duplicate detection using learnable string similarity measures
The problem of identifying approximately duplicate records in databases is an essential step for data cleaning and data integration processes. Most existing approaches have relied...
Mikhail Bilenko, Raymond J. Mooney
151
Voted
RECOMB
2006
Springer
16 years 6 months ago
CONTRAlign: Discriminative Training for Protein Sequence Alignment
In this paper, we present CONTRAlign, an extensible and fully automatic framework for parameter learning and protein pairwise sequence alignment using pair conditional random field...
Chuong B. Do, Samuel S. Gross, Serafim Batzoglou
ESEM
2009
ACM
16 years 24 days ago
We need more coverage, stat! classroom experience with the software ICU
For empirical software engineering to reach its fullest potential, we must develop effective, experiential approaches to learning about it in a classroom setting. In this paper, ...
Philip Johnson, Shaoxuan Zhang
ICDE
2008
IEEE
189views Database» more  ICDE 2008»
16 years 21 days ago
Adapting ranking functions to user preference
— Learning to rank has become a popular method for web search ranking. Traditionally, expert-judged examples are the major training resource for machine learned web ranking, whic...
Keke Chen, Ya Zhang, Zhaohui Zheng, Hongyuan Zha, ...
ICCV
2007
IEEE
16 years 18 days ago
Action Recognition from Arbitrary Views using 3D Exemplars
In this paper, we address the problem of learning compact, view-independent, realistic 3D models of human actions recorded with multiple cameras, for the purpose of recognizing th...
Daniel Weinland, Edmond Boyer, Rémi Ronfard