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MOR
2008
81views more  MOR 2008»
13 years 3 months ago
Risk Tuning with Generalized Linear Regression
A framework is set up in which linear regression, as a way of approximating a random variable by other random variables, can be carried out in a variety of ways, which moreover ca...
R. Tyrrell Rockafellar, Stan Uryasev, Michael Zaba...
CORR
2007
Springer
112views Education» more  CORR 2007»
13 years 3 months ago
Learning from compressed observations
— The problem of statistical learning is to construct a predictor of a random variable Y as a function of a related random variable X on the basis of an i.i.d. training sample fr...
Maxim Raginsky
JAR
2008
88views more  JAR 2008»
13 years 3 months ago
Using Theorem Proving to Verify Expectation and Variance for Discrete Random Variables
Statistical quantities, such as expectation (mean) and variance, play a vital role in the present age probabilistic analysis. In this paper, we present some formalization of expect...
Osman Hasan, Sofiène Tahar
FS
2006
66views more  FS 2006»
13 years 3 months ago
Generalized deviations in risk analysis
General deviation measures are introduced and studied systematically for their potential applications to risk management in areas like portfolio optimization and engineering. Such...
R. Tyrrell Rockafellar, Stan Uryasev, Michael Zaba...
CC
2008
Springer
131views System Software» more  CC 2008»
13 years 3 months ago
Exposure-Resilient Extractors and the Derandomization of Probabilistic Sublinear Time
There exists a positive constant < 1 such that for any function T(n) n and for any problem L BPTIME(T(n)), there exists a deterministic algorithm running in poly(T(n)) time w...
Marius Zimand
WSC
2004
13 years 5 months ago
A Unified Approach for Finite-Dimensional, Rare-Event Monte Carlo Simulation
We consider the problem of estimating the small probability that a function of a finite number of random variables exceeds a large threshold. Each input random variable may be lig...
Zhi Huang, Perwez Shahabuddin
CSC
2006
13 years 5 months ago
Statistical Analysis of Linear Random Differential Equation
In this paper, a new method is proposed in order to evaluate the stochastic solution of linear random differential equation. The method is based on the combination of the probabili...
Seifedine Kadry
ICMLA
2007
13 years 5 months ago
Maximum Likelihood Quantization of Genomic Features Using Dynamic Programming
Dynamic programming is introduced to quantize a continuous random variable into a discrete random variable. Quantization is often useful before statistical analysis or reconstruct...
Mingzhou (Joe) Song, Robert M. Haralick, Sté...
EDBT
2009
ACM
173views Database» more  EDBT 2009»
13 years 8 months ago
PROUD: a probabilistic approach to processing similarity queries over uncertain data streams
We present PROUD - A PRObabilistic approach to processing similarity queries over Uncertain Data streams, where the data streams here are mainly time series streams. In contrast t...
Mi-Yen Yeh, Kun-Lung Wu, Philip S. Yu, Ming-Syan C...
ISIPTA
2003
IEEE
13 years 9 months ago
Study of the Probabilistic Information of a Random Set
Given a random set coming from the imprecise observation of a random variable, we study how to model the information about the distribution of this random variable. Specifically,...
Enrique Miranda, Inés Couso, Pedro Gil