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CORR
2011
Springer
182views Education» more  CORR 2011»
14 years 5 months ago
Adaptively Learning the Crowd Kernel
We introduce an algorithm that, given n objects, learns a similarity matrix over all n2 pairs, from crowdsourced data alone. The algorithm samples responses to adaptively chosen t...
Omer Tamuz, Ce Liu, Serge Belongie, Ohad Shamir, A...
ICTAI
2005
IEEE
15 years 7 months ago
ACE: An Aggressive Classifier Ensemble with Error Detection, Correction, and Cleansing
Learning from noisy data is a challenging and reality issue for real-world data mining applications. Common practices include data cleansing, error detection and classifier ensemb...
Yan Zhang, Xingquan Zhu, Xindong Wu, Jeffrey P. Bo...
134
Voted
ALT
1994
Springer
15 years 5 months ago
Program Synthesis in the Presence of Infinite Number of Inaccuracies
Most studies modeling inaccurate data in Gold style learning consider cases in which the number of inaccuracies is finite. The present paper argues that this approach is not reaso...
Sanjay Jain
JIDM
2010
90views more  JIDM 2010»
14 years 8 months ago
A Context-Dependent Supervised Learning Approach to Sentiment Detection in Large Textual Databases
Sentiment detection automatically identifies emotions in textual data. The increasing amount of emotive documents available in corporate databases and on the World Wide Web calls f...
Albert Weichselbraun, Stefan Gindl, Arno Scharl
123
Voted
MM
2009
ACM
277views Multimedia» more  MM 2009»
15 years 8 months ago
Inferring semantic concepts from community-contributed images and noisy tags
In this paper, we exploit the problem of inferring images’ semantic concepts from community-contributed images and their associated noisy tags. To infer the concepts more accura...
Jinhui Tang, Shuicheng Yan, Richang Hong, Guo-Jun ...