This paper presents a cross-based framework of performing local multipoint filtering efficiently. We formulate the filtering process as a local multipoint regression problem, c...
We consider the multiple-response regression problem, where the response is subject to sparse gross errors, in the high-dimensional setup. We propose a tractable regularized M-est...
—Despite the range of applications and successes of evolutionary algorithms, expensive fitness computations often form a critical performance bottleneck. A preferred method of r...
We present a method to discover robust and interpretable sociolinguistic associations from raw geotagged text data. Using aggregate demographic statistics about the authors’ geo...
The paper presents a novel feature extraction technique for face recognition which uses sparse projection axes to compute a lowdimensional representation of face images. The propos...
In this paper, we propose an iterative algorithm for multiple regression with fuzzy variables.While using the standard least-squares criterion as a performance index, we pose the ...
Andrzej Bargiela, Witold Pedrycz, Tomoharu Nakashi...
We consider the regression problem and describe an algorithm approximating the regression function by estimators piecewise constant on the elements of an adaptive partition. The pa...
In the multi-view regression problem, we have a regression problem where the input variable (which is a real vector) can be partitioned into two different views, where it is assum...
We consider a regression problem where target values are given as intervals, and propose a statistical approach to it. Although it is hard to solve the optimization problem direct...