Results 41 to 50 of about 3,138,878 (297)

Maximum Likelihood and the Single Receptor [PDF]

open access: yesPhysical Review Letters, 2009
Biological cells are able to accurately sense chemicals with receptors at their surfaces, allowing cells to move towards sources of attractant and away from sources of repellent. The accuracy of sensing chemical concentration is ultimately limited by the random arrival of particles at the receptors by diffusion.
Endres, RG, Wingreen, NS
openaire   +4 more sources

Dynamic Indoor Localization Using Maximum Likelihood Particle Filtering

open access: yesSensors, 2021
A popular approach for solving the indoor dynamic localization problem based on WiFi measurements consists of using particle filtering. However, a drawback of this approach is that a very large number of particles are needed to achieve accurate results ...
Wenxu Wang, Damián Marelli, Minyue Fu
doaj   +1 more source

Maximum likelihood associative memories [PDF]

open access: yes2013 IEEE Information Theory Workshop (ITW), 2013
Associative memories are structures that store data in such a way that it can later be retrieved given only a part of its content -- a sort-of error/erasure-resilience property. They are used in applications ranging from caches and memory management in CPUs to database engines.
Gripon, Vincent, Rabbat, Michael
openaire   +4 more sources

Maximum likelihood localization: When does it fail?

open access: yesICT Express, 2016
Maximum likelihood is a criterion often used to derive localization algorithms. In particular, in this paper we focus on a distance-based algorithm for the localization of nodes in static wireless networks. Assuming that Ultra Wide Band (UWB) signals are
Stefania Monica, Gianluigi Ferrari
doaj   +1 more source

On maximum-likelihood decoding with circuit-level errors [PDF]

open access: yesQuantum, 2020
Error probability distribution associated with a given Clifford measurement circuit is described exactly in terms of the circuit error-equivalence group, or the circuit subsystem code previously introduced by Bacon, Flammia, Harrow, and Shi. This gives a
Leonid P. Pryadko
doaj   +1 more source

Approximate Profile Maximum Likelihood

open access: yesJ. Mach. Learn. Res., 2017
We propose an efficient algorithm for approximate computation of the profile maximum likelihood (PML), a variant of maximum likelihood maximizing the probability of observing a sufficient statistic rather than the empirical sample. The PML has appealing theoretical properties, but is difficult to compute exactly.
Dmitri S. Pavlichin   +2 more
openaire   +5 more sources

The Density of the Maximum Likelihood Estimator

open access: yesEconometrica, 1999
In this paper we derive an expression for the exact density of the maximum likelihood estimator (MLE) in the case where the MLE is uniquely defined at each point in the sample space by the vanishing of the score vector.
Hillier, G, Armstrong, M
openaire   +2 more sources

A new maximum-likelihood method for template fits

open access: yesEuropean Physical Journal C: Particles and Fields, 2022
A common statistical problem in particle physics is to extract the number of samples which originate from a statistical process in an ensemble containing a mix of several contributing processes. The probability density function of each process is usually
Hans Dembinski, Ahmed Abdelmotteleb
doaj   +1 more source

New maximum likelihood estimators for eukaryotic intron evolution. [PDF]

open access: yesPLoS Computational Biology, 2005
The evolution of spliceosomal introns remains poorly understood. Although many approaches have been used to infer intron evolution from the patterns of intron position conservation, the results to date have been contradictory.
Hung D Nguyen   +2 more
doaj   +2 more sources

Privacy-preserving Maximum Likelihood Estimation for Distributed Data

open access: yesThe Journal of Privacy and Confidentiality, 2010
Recent technological advances enable the collection of huge amounts of data. Commonly, these data are generated, stored, and owned by multiple entities that are unwilling to cede control of their data. This distributed environment requires statistical
Xiaodong Lin, Alan F. Karr
doaj   +1 more source

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