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» Learning from Multiple Sources of Inaccurate Data
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VDB
2000
144views Database» more  VDB 2000»
15 years 4 months ago
BBQ: A Visual Interface for Integrated Browsing and Querying of XML
In this paper we present BBQ (Blended Browsing and Querying), a graphic user interface for seamlessly browsing and querying XML data sources. BBQ displays the structure of multipl...
Kevin D. Munroe, Yannis Papakonstantinou
132
Voted
KDD
2001
ACM
163views Data Mining» more  KDD 2001»
16 years 3 months ago
Learning to recognize brain specific proteins based on low-level features from on-line prediction servers
During the last decade, the area of bioinformatics has produced an overwhelming amount of data, with the recently published draft of the human genome being the most prominent exam...
Henrik Boström, Joakim Cöster, Lars Aske...
131
Voted
TRECVID
2008
15 years 4 months ago
Learning TRECVID'08 High-Level Features from YouTube
Run No. Run ID Run Description infMAP (%) training on TV08 data 1 IUPR-TV-M SIFT visual words with maximum entropy 6.1 2 IUPR-TV-MF SIFT with maximum entropy, fused with color+tex...
Adrian Ulges, Christian Schulze, Markus Koch, Thom...
KDD
2008
ACM
183views Data Mining» more  KDD 2008»
16 years 3 months ago
Knowledge transfer via multiple model local structure mapping
The effectiveness of knowledge transfer using classification algorithms depends on the difference between the distribution that generates the training examples and the one from wh...
Jing Gao, Wei Fan, Jing Jiang, Jiawei Han
136
Voted
CVPR
2009
IEEE
16 years 9 months ago
An Instance Selection Approach to Multiple Instance Learning
Multiple-instance Learning (MIL) is a new paradigm of supervised learning that deals with the classification of bags. Each bag is presented as a collection of instances from whi...
Zhouyu Fu (Australian National University), Antoni...