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» Boosting Kernel Models for Regression
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AAAI
2007
15 years 8 months ago
A Randomized String Kernel and Its Application to RNA Interference
String kernels directly model sequence similarities without the necessity of extracting numerical features in a vector space. Since they better capture complex traits in the seque...
Shibin Qiu, Terran Lane, Ljubomir J. Buturovic
182
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IR
2010
15 years 4 months ago
Adapting boosting for information retrieval measures
Abstract We present a new ranking algorithm that combines the strengths of two previous methods: boosted tree classification, and LambdaRank, which has been shown to be empiricall...
Qiang Wu, Christopher J. C. Burges, Krysta Marie S...
SIGPRO
2010
111views more  SIGPRO 2010»
15 years 1 months ago
Semi-supervised speaker identification under covariate shift
In this paper, we propose a novel semi-supervised speaker identification method that can alleviate the influence of non-stationarity such as session dependent variation, the recor...
Makoto Yamada, Masashi Sugiyama, Tomoko Matsui
CSSC
2008
84views more  CSSC 2008»
15 years 6 months ago
Nonparametric Regression as an Example of Model Choice
Nonparametric regression can be considered as a problem of model choice. In this paper we present the results of a simulation study in which several nonparametric regression techn...
Laurie Davies, Ursula Gather, Henrike Weinert
JMLR
2010
169views more  JMLR 2010»
15 years 1 months ago
Matrix-Variate Dirichlet Process Mixture Models
We are concerned with a multivariate response regression problem where the interest is in considering correlations both across response variates and across response samples. In th...
Zhihua Zhang, Guang Dai, Michael I. Jordan