Arbitrary source models and bayesian codebooks in rate
... degree of freedom, where, in contrast with the case of lossless compression, “freedom” is measured with respect to the class of possible codebook distributions we are allowed to use, and not with respect to the size of the class of sources considered. In view of the recent results in [28], this rate ...
... degree of freedom, where, in contrast with the case of lossless compression, “freedom” is measured with respect to the class of possible codebook distributions we are allowed to use, and not with respect to the size of the class of sources considered. In view of the recent results in [28], this rate ...
Probability metrics applied to problems in portfolio theory
... common stocks. Then the quantity −FX−1 (t) is known as the value-atrisk (VaR) of common stock X at confidence level (1 − t)100%. It is used as a risk measure and represents a loss threshold such that losing more than it happens with probability t. The probability t is also called the tail probabilit ...
... common stocks. Then the quantity −FX−1 (t) is known as the value-atrisk (VaR) of common stock X at confidence level (1 − t)100%. It is used as a risk measure and represents a loss threshold such that losing more than it happens with probability t. The probability t is also called the tail probabilit ...
Section 3 - Electronic Colloquium on Computational Complexity
... size. Moreover, these sizes are a (multiplicative) factor at least log n from each other. Yet, we argue that no non-adaptive deterministic tester making too few queries can distinguish between a random distribution from D1 and one from D2 , as the tuple of samples it will obtain in both cases is alm ...
... size. Moreover, these sizes are a (multiplicative) factor at least log n from each other. Yet, we argue that no non-adaptive deterministic tester making too few queries can distinguish between a random distribution from D1 and one from D2 , as the tuple of samples it will obtain in both cases is alm ...
Tomasz R. Bielecki (Chicago, IL) Marek Rutkowski (Warszawa
... through the standard intensity-based methodology; in particular, it is natural to introduce in this context the state-variables process Y , representing the macroeconomic factors. Thus, it suffices to focus on securities issued by secondary firms, i.e., firms for which the intensity of default depen ...
... through the standard intensity-based methodology; in particular, it is natural to introduce in this context the state-variables process Y , representing the macroeconomic factors. Thus, it suffices to focus on securities issued by secondary firms, i.e., firms for which the intensity of default depen ...
Elements of Probability Theory and Mathematical Statistics
... The modern probability theory is an interesting and most important part of mathematics, which has great achievements and close connections both with classical parts of mathematics ( geometry, mathematical analysis, functional analysis), and its various branches( theory of random processes, theory of ...
... The modern probability theory is an interesting and most important part of mathematics, which has great achievements and close connections both with classical parts of mathematics ( geometry, mathematical analysis, functional analysis), and its various branches( theory of random processes, theory of ...
6= BPP on the hardness of PAC learning On basing ZK
... To do so, one would have to generalize the techniques above to handle the search problem of finding the hidden labelling function rather than simply deciding whether it exists, as well as deal with the fact that in standard PAC learning one does not have access to the circuit generating labelled exa ...
... To do so, one would have to generalize the techniques above to handle the search problem of finding the hidden labelling function rather than simply deciding whether it exists, as well as deal with the fact that in standard PAC learning one does not have access to the circuit generating labelled exa ...
Approximations for Probability Distributions and
... 1.1 Definition. A semi-distance on P is a function d(·, ·) on P ×P, which satisfies (i) and (ii) below. (i) Nonnegativity. For all P1 , P2 ∈ P d(P1 , P2 ) ≥ 0. (ii) Triangle Inequality. For all P1 , P2 , P3 ∈ P d(P1 , P2 ) ≤ d(P1 , P3 ) + d(P3 , P2 ). If a semi-distance satisfies the strictness prop ...
... 1.1 Definition. A semi-distance on P is a function d(·, ·) on P ×P, which satisfies (i) and (ii) below. (i) Nonnegativity. For all P1 , P2 ∈ P d(P1 , P2 ) ≥ 0. (ii) Triangle Inequality. For all P1 , P2 , P3 ∈ P d(P1 , P2 ) ≤ d(P1 , P3 ) + d(P3 , P2 ). If a semi-distance satisfies the strictness prop ...
投影片 1 - National Tsing Hua University
... • Often Gaussian-Legendre (GL) quadrature applied to evaluate the integral equation in SPC • The GL method often produce fast and accurate ARL results when the integration kernel is smooth but unreliable results when the integration kernel is not smooth. • Non-smooth integration kernels could be due ...
... • Often Gaussian-Legendre (GL) quadrature applied to evaluate the integral equation in SPC • The GL method often produce fast and accurate ARL results when the integration kernel is smooth but unreliable results when the integration kernel is not smooth. • Non-smooth integration kernels could be due ...
Probability and Statistics Prof.Dr.Somesh Kumar Department of
... For what values of p a 5 component system is more likely to operate effectively than a 3 component system.So, we have to calculate the probability of a 5 component system working effectively and a 3 component system operating effectively; so, let us use a notation P n, let it be the probability tha ...
... For what values of p a 5 component system is more likely to operate effectively than a 3 component system.So, we have to calculate the probability of a 5 component system working effectively and a 3 component system operating effectively; so, let us use a notation P n, let it be the probability tha ...
Probability and Random Variables Prof. M. Chakraborty Department
... case of two random variables; that is suppose there are two random variable x and y. So, so far we discussed, I mean, earlier the probability density and distribution of a particular random variable, single random variable. Same concepts will now be extended to the case of joint random variable. Now ...
... case of two random variables; that is suppose there are two random variable x and y. So, so far we discussed, I mean, earlier the probability density and distribution of a particular random variable, single random variable. Same concepts will now be extended to the case of joint random variable. Now ...
