This letter proposes a multioutput support vector regression (M-SVR) method for the
simultaneous estimation of different biophysical parameters from remote sensing images …

Partial label learning aims to learn from training examples each associated with a set of
candidate labels, among which only one label is valid for the training example. The common …

This paper addresses the problem of multiple-input multiple-output (MIMO) frequency
nonselective channel estimation. We develop a new method for multiple variable regression …

Label distribution covers a certain number of labels, representing the degree to which each
label describes the instance. When dealing with label ambiguity, label distribution could …

This paper gives an attempt to explore the manifold in the label space for multi-label
learning. Traditional label space is logical, where no manifold exists. In order to study the …

This paper presents a new approach to auto-regressive and moving average (ARMA)
modeling based on the support vector method (SVM) for identification applications. A …

In this communication, we generalize the Support Vector Machines (SVM) for regression
estimation and function approximation to multi-dimensional problems. We propose a multi …

In smart grids, customers are promoted to change their energy consumption patterns by
electricity prices. In fact, in this environment, the electricity price and load consumption are …

Support vector machines (SVMs) are a new nonparametric tool for regression estimation.
We will use this tool to estimate the parameters of a GARCH model for predicting the …

Assessment of the spatial distribution of bedrock level (BL) as the lower boundary of soil
layers is associated with many uncertainties. Increasing our knowledge about the spatial …