Results 1  10
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2,055,733
Probabilistic norms and statistical convergence of random variables
 Surveys Math. Appl
"... Abstract. The paper extends certain stochastic convergence of sequences of Rkvalued random variables (namely, the convergence in probability, in Lp and almost surely) to the context of Evalued random variables. 1 ..."
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Cited by 1 (0 self)
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Abstract. The paper extends certain stochastic convergence of sequences of Rkvalued random variables (namely, the convergence in probability, in Lp and almost surely) to the context of Evalued random variables. 1
Remarks on Uniform Convergence of Random Variables and Statistics
, 2009
"... The aim of this paper is to review and clarify some facts concerning the uniform convergence of statistics like X̄n and random variables like n(X̄n − µ(θ))/σ(θ). We consider convergence in distribution or in probability, uniform with respect to a family of probability distributions. It seems that ..."
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The aim of this paper is to review and clarify some facts concerning the uniform convergence of statistics like X̄n and random variables like n(X̄n − µ(θ))/σ(θ). We consider convergence in distribution or in probability, uniform with respect to a family of probability distributions. It seems
Random forests
 Machine Learning
, 2001
"... Abstract. Random forests are a combination of tree predictors such that each tree depends on the values of a random vector sampled independently and with the same distribution for all trees in the forest. The generalization error for forests converges a.s. to a limit as the number of trees in the fo ..."
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Cited by 3443 (2 self)
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Abstract. Random forests are a combination of tree predictors such that each tree depends on the values of a random vector sampled independently and with the same distribution for all trees in the forest. The generalization error for forests converges a.s. to a limit as the number of trees
PROBABILITY INEQUALITIES FOR SUMS OF BOUNDED RANDOM VARIABLES
, 1962
"... Upper bounds are derived for the probability that the sum S of n independent random variables exceeds its mean ES by a positive number nt. It is assumed that the range of each summand of S is bounded or bounded above. The bounds for Pr(SES> nt) depend only on the endpoints of the ranges of the s ..."
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Cited by 2169 (2 self)
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Upper bounds are derived for the probability that the sum S of n independent random variables exceeds its mean ES by a positive number nt. It is assumed that the range of each summand of S is bounded or bounded above. The bounds for Pr(SES> nt) depend only on the endpoints of the ranges
On a test of whether one of two random variables is stochasitcally larger than the other
 ANNALS OF MATHEMATICAL STATISTICS
, 1947
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Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
, 2001
"... Variable selection is fundamental to highdimensional statistical modeling, including nonparametric regression. Many approaches in use are stepwise selection procedures, which can be computationally expensive and ignore stochastic errors in the variable selection process. In this article, penalized ..."
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Cited by 903 (60 self)
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Variable selection is fundamental to highdimensional statistical modeling, including nonparametric regression. Many approaches in use are stepwise selection procedures, which can be computationally expensive and ignore stochastic errors in the variable selection process. In this article, penalized
SelfSimilarity Through HighVariability: Statistical Analysis of Ethernet LAN Traffic at the Source Level
 IEEE/ACM TRANSACTIONS ON NETWORKING
, 1997
"... A number of recent empirical studies of traffic measurements from a variety of working packet networks have convincingly demonstrated that actual network traffic is selfsimilar or longrange dependent in nature (i.e., bursty over a wide range of time scales)  in sharp contrast to commonly made tr ..."
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Cited by 733 (24 self)
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traffic modeling assumptions. In this paper, we provide a plausible physical explanation for the occurrence of selfsimilarity in LAN traffic. Our explanation is based on new convergence results for processes that exhibit high variability (i.e., infinite variance) and is supported by detailed statistical
The unity and diversity of executive functions and their contributions to complex “Frontal Lobe” tasks: a latent variable analysis
 COGNIT PSYCHOL
, 2000
"... This individual differences study examined the separability of three often postulated executive functions—mental set shifting ("Shifting"), information updating and monitoring ("Updating"), and inhibition of prepotent responses ("Inhibition")—and their roles in complex ..."
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Cited by 631 (9 self)
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Sorting Test (WCST), Tower of Hanoi (TOH), random number generation (RNG), operation span, and dual tasking. Confirmatory factor analysis indicated that the three target executive functions are moderately correlated with one another, but are clearly separable. Moreover, structural equation modeling
A simple distributed autonomous power control algorithm and its convergence
 IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
, 1993
"... For wireless cellular communication systems, one seeks a simple effective means of power control of signals associated with randomly dispersed users that are reusing a single channel in different cells. By effecting the lowest interference environment, in meeting a required minimum signaltointerf ..."
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Cited by 467 (3 self)
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For wireless cellular communication systems, one seeks a simple effective means of power control of signals associated with randomly dispersed users that are reusing a single channel in different cells. By effecting the lowest interference environment, in meeting a required minimum signal
The highly irregular firing of cortical cells is inconsistent with temporal integration of random EPSPs
 Journal of Neuroscience
, 1993
"... How random is the discharge pattern of cortical neurons? We examined recordings from primary visual cortex (Vl; Knierim and Van Essen, 1992) and extrastriate cortex (MT; Newsome et al., 1989a) of awake, behaving macaque monkey and compared them to analytical predictions. For nonbursting cells firi ..."
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Cited by 447 (11 self)
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in virtually all Vl and MT neurons was nearly consistent with a completely random process (e.g., C, = 1). We tried to model this high variability by small, independent, and random EPSPs converging onto a leaky integrateandfire neuron (Knight, 1972). Both this and related models
Results 1  10
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2,055,733