Support Vector Regression (SVR) has been a long standing problem in machine learning, and gains its popularity on various computer vision tasks. In this paper, we propose a structured support vector regression framework by extending the max-margin principle to incorporate spatial correlations among neighboring pixels. The objective function in our framework considers both label information and ...

Support Vector Regression (SVR), a category for Support Vector Machine (SVM) attempts to minimize the generalization error bound so as to achieve generalized performance. Regression is that of finding a function which approximates mapping from an input domain to the real numbers on the basis of a training sample. Support vector regression is the natural extension of large margin kernel methods ...

Wepropose the reduced twin support vector regressor (RTSVR) that uses the notion of rectangular kernels to obtain significant improvements in execution time over the twin support vector regressor (TSVR), thus facilitating its application to larger sized datasets. & 2011 Elsevier B.V. All rights reserved.

We address the distribution regression problem (DRP): regressing on the (possibly infinite dimensional) domain of probability measures, in the two-stage sampled setup when only samples from the distributions are observable. The DRP formulation offers a unified framework for several important tasks in statistics and machine learning including for example, drug activity prediction, aerosol optica...

We propose a new approach exploiting the failure risk (node, link or Shared Risk Link Group) structures to enhance the backup path computation. Upon failure, our approach classifies the backup paths into two categories: operative backup paths and inoperative backup paths. An operative backup path is an active backup path which really receives traffic of some affected communications while an ino...

Reservoir permeability is a critical parameter for characterization of the hydrocarbon reservoirs. In fact, determination of permeability is a crucial task in reserve estimation, production and development. Traditional methods for permeability prediction are well log and core data analysis which are very expensive and time-consuming. Well log data is an alternative approach for prediction of pe...

Support Vector Regression (SVR) solves regression problems based on the concept of Support Vector Machine (SVM). In this paper, a new model of SVR with probabilistic constraints is proposed that any of output data and bias are considered the random variables with uniform probability functions. Using the new proposed method, the optimal hyperplane regression can be obtained by solving a quadrati...

Memprediksi laju penguapan memiliki manfaat yang luas dalam berbagai aplikasi seperti manajemen sumber daya air, pertanian, dan lingkungan hidup. Namun untuk mendapatkan data lengkap akurat mempelajari tantangan tersendiri. Selain itu, rendahnya tingkat linieritas antara faktor meteorologi lainnya di wilayah tropis dapat menyebabkan hasil prediksi bervariasi. Tujuan dari penelitian ini adalah m...