TSP
2010
13 years 6 months ago
2010
Consider the problem of estimating the parameters of multiple polynomial phase signals observed by a sensor array. In practice, it is difficult to maintain a precisely calibrated a...
SOCIALCOM
2010
13 years 9 months ago
2010
The huge size of online social networks (OSNs) makes it prohibitively expensive to precisely measure any properties which require the knowledge of the entire graph. To estimate the...
PR
2002
13 years 11 months ago
2002
The satellite image deconvolution problem is ill-posed and must be regularized. Herein, we use an edge-preserving regularization model using a ' function, involving two hyper...
TIFS
2008
13 years 11 months ago
2008
In this paper, we provide a unified framework for identifying the source digital camera from its images and for revealing digitally altered images using photo-response nonuniformit...
TIFS
2008
13 years 11 months ago
2008
This paper presents a method for detection of double JPEG compression and a maximum likelihood estimator of the primary quality factor. These methods are essential for construction...
CORR
2007
Springer
13 years 11 months ago
2007
Springer
— We use statistical estimates of the entropy rate of spike train data in order to make inferences about the underlying structure of the spike train itself. We first examine a n...
DICTA
2003
14 years 25 days ago
2003
In this paper, we present an interpretation of the Maximum Likelihood Estimator (MLE) and the Delogne-K˚asa Estimator (DKE) for circle-parameter estimation via convolution. Under ...
ACL
2006
14 years 25 days ago
2006
We investigate generalizations of the allsubtrees "DOP" approach to unsupervised parsing. Unsupervised DOP models assign all possible binary trees to a set of sentences ...
BMVC
2002
14 years 1 months ago
2002
We address the 3D reconstruction of scenes in which some planarity, collinearity, symmetry and other geometric properties are known
COLT
2006
Springer
14 years 3 months ago
2006
Springer
Abstract. We present an improved version of random projections that takes advantage of marginal norms. Using a maximum likelihood estimator (MLE), marginconstrained random projecti...