Results 1  10
of
116
On the constancy of Internet path properties
 In Proceedings of ACM SIGCOMM Internet Measurement Workshop
, 2001
"... Abstract — Many Internet protocols and operational procedures use measurements to guide future actions. This is an effective strategy if the quantities being measured exhibit a degree of constancy: that is, in some fundamental sense, they are not changing. In this paper we explore three different no ..."
Abstract

Cited by 297 (15 self)
 Add to MetaCart
Abstract — Many Internet protocols and operational procedures use measurements to guide future actions. This is an effective strategy if the quantities being measured exhibit a degree of constancy: that is, in some fundamental sense, they are not changing. In this paper we explore three different notions of constancy: mathematical, operational, and predictive. Using a large measurement dataset gathered from the NIMI infrastructure, we then apply these notions to three Internet path properties: loss, delay, and throughput. Our aim is to provide guidance as to when assumptions of various forms of constancy are sound, versus when they might prove misleading. I.
On the universality and cultural specificity of emotion recognition: A metaanalysis
 Psychological Bulletin
, 2002
"... All intext references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately. ..."
Abstract

Cited by 174 (22 self)
 Add to MetaCart
(Show Context)
All intext references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately.
Rational approximations to rational models: Alternative algorithms for category learning
"... Rational models of cognition typically consider the abstract computational problems posed by the environment, assuming that people are capable of optimally solving those problems. This differs from more traditional formal models of cognition, which focus on the psychological processes responsible fo ..."
Abstract

Cited by 60 (17 self)
 Add to MetaCart
(Show Context)
Rational models of cognition typically consider the abstract computational problems posed by the environment, assuming that people are capable of optimally solving those problems. This differs from more traditional formal models of cognition, which focus on the psychological processes responsible for behavior. A basic challenge for rational models is thus explaining how optimal solutions can be approximated by psychological processes. We outline a general strategy for answering this question, namely to explore the psychological plausibility of approximation algorithms developed in computer science and statistics. In particular, we argue that Monte Carlo methods provide a source of “rational process models” that connect optimal solutions to psychological processes. We support this argument through a detailed example, applying this approach to Anderson’s (1990, 1991) Rational Model of Categorization (RMC), which involves a particularly challenging computational problem. Drawing on a connection between the RMC and ideas from nonparametric Bayesian statistics, we propose two alternative algorithms for approximate inference in this model. The algorithms we consider include Gibbs sampling, a procedure
Bayesian models of cognition
"... For over 200 years, philosophers and mathematicians have been using probability theory to describe human cognition. While the theory of probabilities was first developed as a means of analyzing games of chance, it quickly took on a larger and deeper significance as a formal account of how rational a ..."
Abstract

Cited by 54 (2 self)
 Add to MetaCart
(Show Context)
For over 200 years, philosophers and mathematicians have been using probability theory to describe human cognition. While the theory of probabilities was first developed as a means of analyzing games of chance, it quickly took on a larger and deeper significance as a formal account of how rational agents should reason in situations of uncertainty
Efficient Measurement of the Percolation Threshold for Fully Penetrable Discs
, 2000
"... We study the percolation threshold for fully penetrable discs by measuring the average location of the frontier for a statistically inhomogeneous distribution of fully penetrable discs. We use two different algorithms to efficiently simulate the frontier, including the continuum analogue of an algor ..."
Abstract

Cited by 44 (0 self)
 Add to MetaCart
We study the percolation threshold for fully penetrable discs by measuring the average location of the frontier for a statistically inhomogeneous distribution of fully penetrable discs. We use two different algorithms to efficiently simulate the frontier, including the continuum analogue of an algorithm previously used for gradient percolation on a square lattice. We find that # c 0.676 339 0.000 004, thus providing an extra significant digit of accuracy to this constant.
Coevolving protein residues: maximum likelihood identification and relationship to structure
 J. Mol. Biol
, 1999
"... There has been a great deal of recent research on ..."
W: Regularities of contextdependent codon bias in eukaryotic genes
 Nucleic Acids Res
"... Nucleotides surrounding a codon influence the choice of this particular codon from among the group of possible synonymous codons. The strongest influence on codon usage arises from the nucleotide immediately following the codon and is known as the N1 context. We studied the relative abundance of cod ..."
Abstract

Cited by 23 (1 self)
 Add to MetaCart
(Show Context)
Nucleotides surrounding a codon influence the choice of this particular codon from among the group of possible synonymous codons. The strongest influence on codon usage arises from the nucleotide immediately following the codon and is known as the N1 context. We studied the relative abundance of codons with N1 contexts in genes from four eukaryotes for which the entire genomes have been sequenced: Homo sapiens, Drosophila melanogaster, Caenorhabditis elegans and Arabidopsis thaliana. For all the studied organisms it was found that 90 % of the codons have a statistically significant N1 contextdependent codon bias. The relative abundance of each codon with an N1 context was compared with the relative abundance of the same 4mer oligonucleotide in the whole genome. This comparison showed that in about half of all cases the contextdependent codon bias could not be explained by the sequence composition of the genome. Ranking statistics were applied to compare contextdependent codon biases for codons from different synonymous groups. We found regularities in N1 contextdependent codon bias with respect to the codon nucleotide composition. Codons with the same nucleotides in the second and third positions and the same N1 context have a statistically significant correlation of their relative abundances.
Arlequin ver 3.1  An Integrated Software Package for Population Genetics Data Analysis
, 2006
"... ..."
The influence of categories on perception: explaining the perceptual magnet effect as optimal statistical inference
 PSYCHOLOGICAL REVIEW
, 2009
"... A variety of studies have demonstrated that organizing stimuli into categories can affect the way the stimuli are perceived. We explore the influence of categories on perception through one such phenomenon, the perceptual magnet effect, in which discriminability between vowels is reduced near protot ..."
Abstract

Cited by 19 (5 self)
 Add to MetaCart
(Show Context)
A variety of studies have demonstrated that organizing stimuli into categories can affect the way the stimuli are perceived. We explore the influence of categories on perception through one such phenomenon, the perceptual magnet effect, in which discriminability between vowels is reduced near prototypical vowel sounds. We present a Bayesian model to explain why this reduced discriminability might occur: It arises as a consequence of optimally solving the statistical problem of perception in noise. In the optimal solution to this problem, listeners’ perception is biased toward phonetic category means because they use knowledge of these categories to guide their inferences about speakers ’ target productions. Simulations show that model predictions closely correspond to previously published human data, and novel experimental results provide evidence for the predicted link between perceptual warping and noise. The model unifies several previous accounts of the perceptual magnet effect and provides a framework for exploring categorical effects in other domains.