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ICML
2006
IEEE
16 years 6 months ago
Bayesian regression with input noise for high dimensional data
This paper examines high dimensional regression with noise-contaminated input and output data. Goals of such learning problems include optimal prediction with noiseless query poin...
Jo-Anne Ting, Aaron D'Souza, Stefan Schaal
ICML
2005
IEEE
16 years 6 months ago
Ensembles of biased classifiers
We propose a novel ensemble learning algorithm called Triskel, which has two interesting features. First, Triskel learns an ensemble of classifiers, each biased to have high preci...
Andreas Heß, Nicholas Kushmerick, Rinat Khou...
WWW
2009
ACM
16 years 6 months ago
Visual diversification of image search results
Due to the reliance on the textual information associated with an image, image search engines on the Web lack the discriminative power to deliver visually diverse search results. ...
Reinier H. van Leuken, Lluis Garcia Pueyo, Ximena ...
KDD
2009
ACM
156views Data Mining» more  KDD 2009»
16 years 6 months ago
Query result clustering for object-level search
Query result clustering has recently attracted a lot of attention to provide users with a succinct overview of relevant results. However, little work has been done on organizing t...
Jongwuk Lee, Seung-won Hwang, Zaiqing Nie, Ji-Rong...
KDD
2007
ACM
139views Data Mining» more  KDD 2007»
16 years 6 months ago
Raising the baseline for high-precision text classifiers
Many important application areas of text classifiers demand high precision and it is common to compare prospective solutions to the performance of Naive Bayes. This baseline is us...
Aleksander Kolcz, Wen-tau Yih