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ICMLA
2009
13 years 5 months ago
A Syllable-Level Probabilistic Framework for Bird Species Identification
In this paper, we present new probabilistic models for identifying bird species from audio recordings. We introduce the independent syllable model and consider two ways of aggregat...
Balaji Lakshminarayanan, Raviv Raich, Xiaoli Fern
PAMI
2011
13 years 2 months ago
Learning a Family of Detectors via Multiplicative Kernels
—Object detection is challenging when the object class exhibits large within-class variations. In this work, we show that foreground-background classification (detection) and wit...
Quan Yuan, Ashwin Thangali, Vitaly Ablavsky, Stan ...
KDD
2004
ACM
139views Data Mining» more  KDD 2004»
14 years 8 months ago
Learning a complex metabolomic dataset using random forests and support vector machines
Metabolomics is the omics science of biochemistry. The associated data include the quantitative measurements of all small molecule metabolites in a biological sample. These datase...
Young Truong, Xiaodong Lin, Chris Beecher
CIKM
2006
Springer
13 years 11 months ago
Coupling feature selection and machine learning methods for navigational query identification
It is important yet hard to identify navigational queries in Web search due to a lack of sufficient information in Web queries, which are typically very short. In this paper we st...
Yumao Lu, Fuchun Peng, Xin Li, Nawaaz Ahmed
KDD
2000
ACM
133views Data Mining» more  KDD 2000»
13 years 11 months ago
Data selection for support vector machine classifiers
The problem of extracting a minimal number of data points from a large dataset, in order to generate a support vector machine (SVM) classifier, is formulated as a concave minimiza...
Glenn Fung, Olvi L. Mangasarian