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ICDM
2005
IEEE
185views Data Mining» more  ICDM 2005»
15 years 9 months ago
Semi-Supervised Mixture of Kernels via LPBoost Methods
We propose an algorithm to construct classification models with a mixture of kernels from labeled and unlabeled data. The derived classifier is a mixture of models, each based o...
Jinbo Bi, Glenn Fung, Murat Dundar, R. Bharat Rao
AAAI
2011
14 years 4 months ago
Logistic Methods for Resource Selection Functions and Presence-Only Species Distribution Models
In order to better protect and conserve biodiversity, ecologists use machine learning and statistics to understand how species respond to their environment and to predict how they...
Steven Phillips, Jane Elith
NIPS
2007
15 years 5 months ago
Selecting Observations against Adversarial Objectives
In many applications, one has to actively select among a set of expensive observations before making an informed decision. Often, we want to select observations which perform well...
Andreas Krause, H. Brendan McMahan, Carlos Guestri...
PAMI
2007
118views more  PAMI 2007»
15 years 3 months ago
Learning to Transform Time Series with a Few Examples
We describe a semi-supervised regression algorithm that learns to transform one time series into another time series given examples of the transformation. This algorithm is applie...
Ali Rahimi, Ben Recht, Trevor Darrell
ICPR
2000
IEEE
16 years 5 months ago
On Gaussian Radial Basis Function Approximations: Interpretation, Extensions, and Learning Strategies
In this paper we focus on an interpretation of Gaussian radial basis functions (GRBF) which motivates extensions and learning strategies. Specifically, we show that GRBF regressio...
Mário A. T. Figueiredo