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12,444
Random Systematic Exact Value
"... We consider a technique to determine the initial beam conditions of the DARHT II accelerator by measuring the beam size under three different magnetic transport settings. This may be time gated to resolve the parameters as a function of time within the 2000 nsec pulse. This technique leads to three ..."
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We consider a technique to determine the initial beam conditions of the DARHT II accelerator by measuring the beam size under three different magnetic transport settings. This may be time gated to resolve the parameters as a function of time within the 2000 nsec pulse. This technique leads to three equations in three unknowns with solution giving the accelerator exit beam radius, tilt, and emittance. We find that systematic errors cancel and so are not a problem in unfolding the initial beam conditions. Random uncorrelated shot to shot errors can be managed by one of three strategies: 1) make the transport system optically demagnifying; 2) average over many individual shots; or 3) make the random uncorrelated shot to shot errors sufficiently small.
Some Exact Values of Sr
"... In Problem 07003, Hongwei Chen requests a general formula in terms of the digamma function for the sum of the series n=1 ..."
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In Problem 07003, Hongwei Chen requests a general formula in terms of the digamma function for the sum of the series n=1
Exact Matrix Completion via Convex Optimization
, 2008
"... We consider a problem of considerable practical interest: the recovery of a data matrix from a sampling of its entries. Suppose that we observe m entries selected uniformly at random from a matrix M. Can we complete the matrix and recover the entries that we have not seen? We show that one can perfe ..."
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Cited by 873 (26 self)
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by solving a simple convex optimization program. This program finds the matrix with minimum nuclear norm that fits the data. The condition above assumes that the rank is not too large. However, if one replaces the 1.2 exponent with 1.25, then the result holds for all values of the rank. Similar results hold
On some exact values of threecolor . . .
, 2012
"... For graphs G1, G2, G3, the threecolor Ramsey number R(G1, G2, G3) is the smallest integer n such that if we arbitrarily color the edges of the complete graph of order n with 3 colors, then it contains a monochromatic copy of Gi in color i, for some 1 ≤ i ≤ 3. First, we prove that the conjectured eq ..."
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equality R3(C2n, C2n, C2n) = 4n, if true, implies that R3(P2n+1, P2n+1, P2n+1) = 4n + 1 for all n ≥ 3. We also obtain two new exact values R(P8, P8, P8) = 14 and R(P9, P9, P9) = 17, furthermore we do so without help of computer algorithms. Our results agree with a formula R(Pn, Pn, Pn) = 2n−2+(n mod 2
1 MORE EXACT VALUES OF THE HYPERBOLIC FUNCTIONS
"... In a previous paper [3] many exact values of the hyperbolic functions were found. It was shown that if n is any integer, 2 ..."
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In a previous paper [3] many exact values of the hyperbolic functions were found. It was shown that if n is any integer, 2
Finding exact values for infinite sums
 this MAGAZINE
, 1999
"... [1]: From the wellknown results, ..."
An Exact Value for Avogadro’s Number
"... Avogadro’s number, NA, is the fundamental physical constant that links the macroscopic physical world of objects that we can see and feel with the submicroscopic, invisible world of atoms. In theory, NA specifies the exact number of atoms in a palmsized specimen of a physical element such as carbon ..."
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Cited by 1 (1 self)
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Avogadro’s number, NA, is the fundamental physical constant that links the macroscopic physical world of objects that we can see and feel with the submicroscopic, invisible world of atoms. In theory, NA specifies the exact number of atoms in a palmsized specimen of a physical element
Regression Shrinkage and Selection Via the Lasso
 JOURNAL OF THE ROYAL STATISTICAL SOCIETY, SERIES B
, 1994
"... We propose a new method for estimation in linear models. The "lasso" minimizes the residual sum of squares subject to the sum of the absolute value of the coefficients being less than a constant. Because of the nature of this constraint it tends to produce some coefficients that are exactl ..."
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Cited by 4212 (49 self)
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We propose a new method for estimation in linear models. The "lasso" minimizes the residual sum of squares subject to the sum of the absolute value of the coefficients being less than a constant. Because of the nature of this constraint it tends to produce some coefficients
Dynamic Bayesian Networks: Representation, Inference and Learning
, 2002
"... Modelling sequential data is important in many areas of science and engineering. Hidden Markov models (HMMs) and Kalman filter models (KFMs) are popular for this because they are simple and flexible. For example, HMMs have been used for speech recognition and biosequence analysis, and KFMs have bee ..."
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Cited by 770 (3 self)
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random variable. DBNs generalize KFMs by allowing arbitrary probability distributions, not just (unimodal) linearGaussian. In this thesis, I will discuss how to represent many different kinds of models as DBNs, how to perform exact and approximate inference in DBNs, and how to learn DBN models from
The theory of planned behavior
 Organizational Behavior and Human Decision Processes
, 1991
"... Research dealing with various aspects of * the theory of planned behavior (Ajzen, 1985, 1987) is reviewed, and some unresolved issues are discussed. In broad terms, the theory is found to be well supported by empirical evidence. Intentions to perform behaviors of different kinds can be predicted wit ..."
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Cited by 2754 (9 self)
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to be related to appropriate sets of salient behavioral, normative, and control beliefs about the behavior, but the exact nature of these relations is still uncertain. Expectancy — value formulations are found to be only partly successful in dealing with these relations. Optimal rescaling of expectancy
Results 1  10
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12,444