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where { }d is the matrix operator, which replaces all nondiagonal elements with zero As written, E(s) is not well de ned at s = 0 since I T (0) has an eigenvalue of 0 and is not invertible There are two distinct ways of modifying (932) to compute rst-passage transmittances that converge in a neighborhood of zero The rst method inverts [I T (s)] in terms of its adjoint matrices and is discussed in Butler and Huzurbazar (2000) The second method consists of making the destination state an absorbing state We discuss only the second method here Consider rst passage from arbitrary state i to state j = i in the reducible chain described above with transmittances given by (929).

14.1 What are the two basic things that humans can learn 14.2 What are the two basic ways in which programs can learn 14.3 What is the simplest way to form new rules 14.4 Give an example of a new rule formed as in Question 14.3. 14.5 What FLOPS commands relevant to learning can be executed in the consequent of a rule 14.6 What kinds of rules are needed if expert knowledge is stored in a database rather than in rules Which of the example programs use such rules 14.7 We have said that programs can learn from experience either by adding new rules or by adding to a database of expert factual knowledge. If either of these methods could be employed in a particular problem, which method is to be preferred Why 14.8 Suppose that the rule or datum we have learned does not t into a prede ned format. What technique can we use to create completely arbitrary rules or data

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tum and has to be run as a project, he appoints the person who has been closest to him on the project, lets go of the reins completely, and applauds from the sidelines. This is a big idea for senior leaders. There are thousands of books on project management but none of any note on project leadership. The role of top leader involvement is to provide muscle without interference so that projects can get a fast start (e.g., allocated resources, priority status, and overall focus). The other significant moment of project leadership is the handoff at the right time, to the right lieutenant, and with the right resources. The last significant point of this lesson is to pick the right projects to be involved in. Such projects should be top-focus areas that have measurable impact on growing or managing the dream and that will be unifying adding to pride and positioning. Figure 7.3 shows a map to help with this from the view of the RE/MAX case on how to pick projects for leaders to be involved in.

The rst passage transmittance to state j is unaffected by making state j absorbing, and a bene t of this is that the determinant |I T (0)| is made positive State j is made absorbing by modifying matrix T so that the row corresponding to the j th state consists entirely of zeros Note that this holds in the matrix of owgraph transmittances (929) The matrix I T (s) is now invertible in a neighborhood of s = 0, and therefore expression (932) is well de ned in a neighborhood of s = 0 For our problem, to compute the MGF of the waiting time from 0 6, we need only E06 (s) from this formulation We use maple to compute M(s) = E06 using the transmittances from (929), and to compute K (s) = dEij (s)/ds and K (s) = d 2 Eij (s)/ds 2 .

3Q99

Complete data for this M/G/1 queuing system are simulated using = 04, 1 = 3, and 2 = 4 The likelihood is comprised of three separate contributions: 1 Let r1 be the number of transitions observed from 0 1 In the data, r1 = 5 This contributes ve independent Exp(5 ) variates with a total waiting time of 137 2 Let r2 be the observed number of radios that are repaired in total In the data, r2 = 116 This contributes 116 independent IG( 1 , 2 ) terms as t1 , , t116 with minimally suf cient statistics u1 = ti 1 = 1660 and u2 = ti = 866..

C.A.R. Hoare, The Emperor s Old Clothes, The 1980 ACM Turing Award Lecture, Communications of the ACM 24 (2): February 1981.

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