Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Kamiar Rahnama Rad"'
Publikováno v:
PLoS ONE, Vol 19, Iss 1, p e0295499 (2024)
IntroductionThe prevalence of type 2 Diabetes Mellitus (T2DM) is 2-3 times greater among Mexican Americans than non-Latino whites, and Mexican Americans are more likely to develop T2DM at younger ages and experience higher rates of complications. Soc
Externí odkaz:
https://doaj.org/article/a984ac3322184bfa96e48eccccd266b8
Publikováno v:
IEEE Transactions on Information Theory. 67:5997-6030
Risk estimation is at the core of many learning systems. The importance of this problem has motivated researchers to propose different schemes, such as cross validation, generalized cross validation, and Bootstrap. The theoretical properties of such
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a468483d5445d68b5398cd859fb17ca0
https://doi.org/10.1109/tit.2021.3095375
https://doi.org/10.1109/tit.2021.3095375
Autor:
Arian Maleki, Kamiar Rahnama Rad
Publikováno v:
Journal of the Royal Statistical Society Series B: Statistical Methodology. 82:965-996
Summary The paper considers the problem of out-of-sample risk estimation under the high dimensional settings where standard techniques such as K-fold cross-validation suffer from large biases. Motivated by the low bias of the leave-one-out cross-vali
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d6cb76f13a198e54a40ac96cfc47fa71
https://doi.org/10.1111/rssb.12374
https://doi.org/10.1111/rssb.12374
Publikováno v:
Journal of Computational and Graphical Statistics. 23:316-339
Kalman filtering-smoothing is a fundamental tool in statistical time-series analysis. However, standard implementations of the Kalman filter-smoother require O(d3) time and O(d2) space per time step, where d is the dimension of the state variable, an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7257713c7d9feffc33b08959f9573932
https://doi.org/10.1080/10618600.2012.760461
https://doi.org/10.1080/10618600.2012.760461
Publikováno v:
IEEE Journal of Selected Topics in Signal Processing. 7:358-369
This paper focuses on a model of opinion formation over networks with continuously flowing new information and studies the relationship between the network and information structures and agents' ability to reach agreement. At each time period, agents
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4f21b2b733c02cdad42f539dc9ed8e18
https://doi.org/10.1109/jstsp.2013.2246764
https://doi.org/10.1109/jstsp.2013.2246764
Publikováno v:
Ann. Appl. Stat. 11, no. 2 (2017), 598-637
A common analytical problem in neuroscience is the interpretation of neural activity with respect to sensory input or behavioral output. This is typically achieved by regressing measured neural activity against known stimuli or behavioral variables t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1ba6d659723799e53b767505d0219351
Autor:
Kamiar Rahnama Rad
Publikováno v:
IEEE Transactions on Information Theory. 57:4672-4679
Consider the n-dimensional vector y=Xβ+e where β ∈ \BBRp has only k nonzero entries and e ∈ \BBRn is a Gaussian noise. This can be viewed as a linear system with sparsity constraints corrupted by noise, where the objective is to estimate the sp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::58a75d2187116ec7680f7cbed7016ee4
https://doi.org/10.1109/tit.2011.2145670
https://doi.org/10.1109/tit.2011.2145670
Publikováno v:
Neural Computation. 21:1203-1243
There has recently been a great deal of interest in inferring network connectivity from the spike trains in populations of neurons. One class of useful models that can be fit easily to spiking data is based on generalized linear point process models
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d21c62f13e897d751a6c0c3593a08d15
https://doi.org/10.1162/neco.2008.04-08-757
https://doi.org/10.1162/neco.2008.04-08-757
Publikováno v:
ACC
We analyze a model of social learning in which agents desire to identify an unknown state of the world using both their private observations and information they obtain when communicating with agents in their social neighborhood. Every agent holds a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::18cd7c6e12fd0950d523af4bf4010c80
https://doi.org/10.1109/acc.2012.6315271
https://doi.org/10.1109/acc.2012.6315271
Publikováno v:
CISS
Sequential Monte Carlo (“particle filtering”) methods provide a powerful set of tools for recursive optimal Bayesian filtering in state-space models. However, these methods are based on importance sampling, which is known to be non-robust in seve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cd65c0a7c85507848f4db507085899cc
https://doi.org/10.1109/ciss.2012.6310772
https://doi.org/10.1109/ciss.2012.6310772