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SAC
2006
ACM
14 years 2 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
IJCV
2008
266views more  IJCV 2008»
13 years 8 months ago
Learning to Recognize Objects with Little Supervision
This paper shows (i) improvements over state-of-the-art local feature recognition systems, (ii) how to formulate principled models for automatic local feature selection in object c...
Peter Carbonetto, Gyuri Dorkó, Cordelia Sch...
SEMWEB
2004
Springer
14 years 2 months ago
METEOR-S Web Service Annotation Framework with Machine Learning Classification
Researchers have recognized the need for more expressive descriptions of Web services. Most approaches have suggested using ontologies to either describe the Web services or to an...
Nicole Oldham, Christopher Thomas, Amit P. Sheth, ...
EMNLP
2011
12 years 8 months ago
Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions
We introduce a novel machine learning framework based on recursive autoencoders for sentence-level prediction of sentiment label distributions. Our method learns vector space repr...
Richard Socher, Jeffrey Pennington, Eric H. Huang,...
KDD
2009
ACM
266views Data Mining» more  KDD 2009»
14 years 3 months ago
OpinionMiner: a novel machine learning system for web opinion mining and extraction
Merchants selling products on the Web often ask their customers to share their opinions and hands-on experiences on products they have purchased. Unfortunately, reading through al...
Wei Jin, Hung Hay Ho, Rohini K. Srihari