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LSQR uses the Golub-Kahan bidiagonalization process to solve sparse least-squares
problems with and without regularization. In some cases, projections of the right-hand
side vector are required, r...
Sparse Projections of Medical Images onto Manifolds
Sparse Projections Medical Images Manifolds
2013/5/2
Manifold learning has been successfully applied to a variety of medical imaging problems. Its use in real-time applications requires fast projection onto the low-dimensional space. To this end, out-of...
Topic Discovery through Data Dependent and Random Projections
Topic Discovery through Data Dependent and Random Projections
2013/4/27
We present algorithms for topic modeling based on the geometry of cross-document word-frequency patterns. This perspective gains significance under the so called separability condition. This is a cond...
On Low-Dimensional Projections of High-Dimensional Distributions
Low-Dimensional Projections High-Dimensional Distributions
2011/7/19
Let $P$ be a probability distribution on $q$-dimensional space. The so-called Diaconis-Freedman effect means that for a fixed dimension $d << q$, most $d$-dimensional projections of $P$ look like a sc...
Resistant estimates for high dimensional and functional data based on random projections
Resistant estimates high dimensional functional data based
2011/7/5
In this paper we propose a new robust estimation method based on random projections which is adaptive, produces an automatic robust estimate, while being easy to compute for high or infinite dimension...
Supply Projections for Dentists, Thailand
dental workforce supply projection for dentists dentist requirement projection cohort retention rate dental student drop out rate population per dentist Thailand
2009/10/15
This paper projects the supply of dentists in Thailand for the next 30 years, using the
proposed first year enrollment plans of MoUA and ONEC, in order to compare future supply
with the projected ...
Some multivariate infinitely divisible distributions and their projections
multivariate infinitely divisible distributions projections
2009/9/22
Recently K. Sato constructed an inlinitely divisible
probability distribution p on Rd such that pis not selfdecomposable but
every projection of y to a lower dmensional space is selfdecomposablc.
L...
Network tomography based on 1-D projections
network tomography one dimensional projection identifiability asymptotically efficient
2010/4/29
Network tomography has been regarded as one of the most promising
methodologies for performance evaluation and diagnosis of the massive and
decentralized Internet. This paper proposes a new estimati...