CVPR
2012
IEEE
12 years 2 months ago
2012
IEEE
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...
SIGIR
2011
ACM
13 years 3 months ago
2011
ACM
Query performance prediction is aimed at predicting the retrieval effectiveness that a query will achieve with respect to a particular ranking model. In this paper, we study quer...
ICASSP
2011
IEEE
13 years 3 months ago
2011
IEEE
Constrained Maximum Likelihood Linear Regression (CMLLR) is a widely used speaker adaptation technique in which an affine transform of the features is estimated for each speaker....
ICASSP
2011
IEEE
13 years 3 months ago
2011
IEEE
Solving linear regression problems based on the total least-squares (TLS) criterion has well-documented merits in various applications, where perturbations appear both in the data...
TSP
2010
13 years 7 months ago
2010
Abstract--Frequency hopping (FH) signals have well-documented merits for commercial and military applications due to their near-far resistance and robustness to jamming. Estimating...
PAMI
2010
13 years 7 months ago
2010
In this paper, we present a novel approach of face identification by formulating the pattern recognition problem in terms of linear regression. Using a fundamental concept that pat...
TSP
2008
14 years 9 days ago
2008
In this paper, we consider the problem of estimating an unknown deterministic parameter vector in a linear regression model with random Gaussian uncertainty in the mixing matrix. W...
PR
2006
14 years 10 days ago
2006
: We address the pose mismatch problem which can occur in face verification systems that have only a single (frontal) face image available for training. In the framework of a Bayes...
FSS
2006
14 years 13 days ago
2006
Since Tanaka et al. in 1982 proposed a study in linear regression with a fuzzy model, fuzzy regression analysis has been widely studied and applied in various areas. However, Tana...
IJDMB
2008
14 years 13 days ago
2008
: This paper addresses the sparse data problem in the linear regression model, namely the number of variables is significantly larger than the number of the data points for regress...