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West, J. MSc Thesis, Department of Computer Science, University College London, 1998.

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Final London Travel Demonstrator - Ucl (1999)   (Correct)

....texture map data. The original maps are stored as 2D DXF files with several layers each containing a different type of building structure. We are primarily interested in building outlines, roads centre and building spot height layers. The conversion stage consists of the following major stages [32]: Identifying and repairing building outlines . Building extrusion and roof fitting . Identifying and connecting road centre lines . Fitting roads between buildings . Creating pavements Each building is composed of two or three layers, entrance, middle and optional upper level and each has ....

West, J. MSc Thesis, Department of Computer Science, University College London, 1998.


Message-Optimal Protocols for Byzantine Agreement - Hadzilacos, Halpern (1992)   (10 citations)  (Correct)

....1)t Gamma 1 messages in H v . If t = 1 and n 4 then jR v j n Gamma t Gamma 1 3, and so there are at least n 2t Gamma 1 n t Gamma 1 messages in H v , a contradiction. If n t 2 then jR v j n Gamma t Gamma 1 2, but in this case there is an additional message mentioned in the hypothesis (that received by some process in B and not sent by a process in R v ) So, in this case we have at least (n t Gamma 1) 1 n t Gamma 1 messages in H v , again a contradiction. Claim 4:5:3 Claim 4.5.4: If t 1 and all processes in B receive both their messages from processes in R v then ....

....2 Gamma a 0 Gamma a 1 Gamma crit 0 Gamma crit 1 , which implies that a 0 a 1 crit 0 crit 1 n Gamma 2t. Therefore, a v crit v n Gamma 2t Gamma a v Gamma crit v n Gamma 2t Gamma (n 2t) 2 = n Gamma 6t) 2 t Gamma 1 as wanted (the last inequality follows because, by hypothesis, n 8t Gamma 2) Claim 7:3:4 Claim 7.3.5: b v d v f v f n v g v t Gamma max v Gamma max t v 2crit v Gamma 1 ffi v . Proof: We consider two cases, depending on the number of proper ancestors of the special node. Case (a) The special node has at least t proper ancestors. Let ....

Thesis, Department of Computer Science, University of Toronto, October 1989.


A Weighted Nearest Neighbor Algorithm for Learning with.. - Cost, Salzberg (1993)   (166 citations)  Self-citation (Cost)   (Correct)

....central residue Qian and Sejnowski (1988) and Holley and Karplus (1989) formulated the problem in exactly the same manner. Both of these studies found the optimal window size to be approximately 17 residues (21 was the largest window tested in either study) In a separate statistical study, Cost (1990) found that a window of size five or six is nearly sufficient for uniquely identifying all residues in our data set, as is indicated by Table 3. This table shows the percentage of sequences of a given size which unambiguously (for the entire data set) determine a fold classification for a protein ....

Cost, S. (1990) M.S. Thesis, Department of Computer Science, Johns Hopkins University.


Clusters of Two Player Games and Restricted Determinacy.. - Khoussainov, Yakhnis.. (1997)   (Correct)

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Thesis, Department of Computer Science, Monash University, Melbourne, Australia, August 1990.


Fitting Uncertain Data with NURBS - Wolfgang Heidrich Richard (1997)   (Correct)

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Thesis, Department of Computer Science, University of Waterloo, 1995.


Adaptive Fraud Detection - Fawcett, Foster (1997)   (40 citations)  (Correct)

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D. thesis, Purdue University, Department of Computer Sciences. Available via ftp://coast. cs.purdue.edu/pub/COAST/kumar-phd-intdet.ps.gz. Nilsson, N. J. (1965). Learning machines. New York: McGraw-Hill.


Massively Parallel Simulated Annealing and its Relation to.. - Rudolph (1994)   (9 citations)  (Correct)

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Diploma thesis, University of Dortmund, Department of Computer Science. Szu, H. and R. Hartley (1987a). Fast simulated annealing. Physics Letters A 122 (3/4), 157--162.


A Tutorial Survey of Reinforcement Learning - Keerthi, Ravindran (1995)   (10 citations)  (Correct)

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Thesis, Department of Computer Science, Stanford University, Stanford, CA, USA. L. P. Kaelbling, 1991, Learning in Embedded Systems. MIT Press, Cambridge, MA, USA.

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