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PAMI
2012
8 years 1 months ago
Color Constancy with Spatio-Spectral Statistics
—We introduce an efficient maximum likelihood approach for one part of the color constancy problem: removing from an image the color cast caused by the spectral distribution of ...
Ayan Chakrabarti, Keigo Hirakawa, Todd Zickler
JMLR
2012
8 years 2 months ago
Noise-Contrastive Estimation of Unnormalized Statistical Models, with Applications to Natural Image Statistics
We consider the task of estimating, from observed data, a probabilistic model that is parameterized by a finite number of parameters. In particular, we are considering the situat...
Michael Gutmann, Aapo Hyvärinen
DAGM
2011
Springer
8 years 11 months ago
Putting MAP Back on the Map
Conditional Random Fields (CRFs) are popular models in computer vision for solving labeling problems such as image denoising. This paper tackles the rarely addressed but important ...
Patrick Pletscher, Sebastian Nowozin, Pushmeet Koh...
ICASSP
2011
IEEE
9 years 3 months ago
Multi-sensor estimation and detection of phase-locked sinusoids
This paper proposes a method to compute the likelihood function for the amplitudes and phase shifts of noisily observed phase-locked and amplitude-constrained sinusoids. The sinus...
Christoph Reller, Hans-Andrea Loeliger, Stefano Ma...
ICASSP
2011
IEEE
9 years 3 months ago
Practical limits in RSS-based positioning
Received signal strength (RSS) based source localization papers often ignore the practical effects of range limits in the measurements. In many devices, this results in some senso...
Richard K. Martin, Amanda Sue King, Ryan W. Thomas...
SAC
2011
ACM
9 years 6 months ago
A quasi-Newton acceleration for high-dimensional optimization algorithms
Abstract In many statistical problems, maximum likelihood estimation by an EM or MM algorithm suffers from excruciatingly slow convergence. This tendency limits the application of ...
Hua Zhou, David Alexander, Kenneth Lange
IGARSS
2009
9 years 9 months ago
A Novel STAP Algorithm using Sparse Recovery Technique
A novel STAP algorithm based on sparse recovery technique, called CS-STAP, were presented. Instead of using conventional maximum likelihood estimation of covariance matrix, our met...
Ke Sun, Hao Zhang, Gang Li, Huadong Meng, Xiqin Wa...
TMI
1998
145views more  TMI 1998»
9 years 11 months ago
Maximum Likelihood Estimation of Rician Distribution Parameters
— The problem of parameter estimation from Rician distributed data (e.g., magnitude Magnetic Resonance images) is addressed. The properties of conventional estimation methods are...
Jan Sijbers, Arnold Jan den Dekker, Paul Scheunder...
JSC
2006
102views more  JSC 2006»
9 years 11 months ago
Counting and locating the solutions of polynomial systems of maximum likelihood equations, I
In statistics, mixture models consisting of several component subpopulations are used widely to model data drawn from heterogeneous sources. In this paper, we consider maximum lik...
Max-Louis G. Buot, Donald St. P. Richards
CSDA
2007
105views more  CSDA 2007»
9 years 11 months ago
GSA-based maximum likelihood estimation for threshold vector error correction model
The log-likelihood function of threshold vector error correction models is neither differentiable, nor smooth with respect to some parameters. Therefore, it is very difficult to ...
Zheng Yang, Zheng Tian, Zixia Yuan
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