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COLING
2010
14 years 11 months ago
A Comparison of Models for Cost-Sensitive Active Learning
Active Learning (AL) is a selective sampling strategy which has been shown to be particularly cost-efficient by drastically reducing the amount of training data to be manually ann...
Katrin Tomanek, Udo Hahn

Publication
344views
14 years 2 months ago
Top-k Similarity Join over Multi-valued Objects
The top-k similarity joins have been extensively studied and used in a wide spectrum of applications such as information retrieval, decision making, spatial data analysis and dat...
Wenjie Zhang, Jing Xu, Xin Liang, Ying Zhang, Xuem...
SAC
2006
ACM
15 years 10 months ago
The impact of sample reduction on PCA-based feature extraction for supervised learning
“The curse of dimensionality” is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimension...
Mykola Pechenizkiy, Seppo Puuronen, Alexey Tsymbal
SIGMOD
1997
ACM
166views Database» more  SIGMOD 1997»
15 years 8 months ago
The InfoSleuth Project
The goal of the InfoSleuth project at MCC is to exploit and synthesize new technologies into a uni ed system that retrieves and processes information in an ever-changing network o...
Roberto J. Bayardo Jr., William Bohrer, Richard S....
AIRS
2005
Springer
15 years 10 months ago
A Probabilistic Model for Music Recommendation Considering Audio Features
In order to make personalized recommendations, many collaborative music recommender systems (CMRS) focused on capturing precise similarities among users or items based on user hist...
Qing Li, Sung-Hyon Myaeng, Donghai Guan, Byeong Ma...