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https://cis.temple.edu/~latecki/Courses/CIS2033-Spring12/ElementaryProbabilityforApplications/ch3.pdf
5/36 5 The same result holds if B = “The first die is k” and 2 ≤ k ≤ 6. Carrying this reasoning further, we see that given the outcome lies in A, all five possibilities have the same probability. This should not be surprising. The original probabil-ity is uniform over the 36 possibilities, so when we condition on the occurrence of A, its five outcomes are equally likely.
https://cis.temple.edu/~latecki/Papers/JoPanECAI2024.pdf
This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).
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This course teaches the student to design and create objects in metal, and combine metal with other materials. The course focuses upon both design and technique. The student learns the fundamentals of design, current styles and formal characteristics of jewelry and metal objects through a series of design problems. Basic techniques of metal manipulation are covered from working with pre ...
https://cis.temple.edu/~latecki/Courses/AI-Fall12/Lectures/GreatMatrixIntro.pdf
and their associatedeigenvectorsof a matrix describe the geometry of the trans- formation associated with that matrix. Using the multivariate normal, we then develop the multivariate breeders’ equation and examine properties of Gaussian fitness functions. We conclude with some elementary concepts in vector calcu- lus, focusing on derivatives of vectors and finding local extrema of vector ...
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Profiling assessment activities at Temple University Libraries and beyond
https://www.fox.temple.edu/sites/fox/files/documents/CVs/xueming-luo-cv.pdf
Bio: Xueming Luo is the Charles Gilliland Distinguished Chair Professor of Marketing, Professor of Strategy, and Professor of MIS, and Founder/ Director of the Global Institute for Artificial Intelligence & Business Analytics in the Fox School of Business at Temple University. He is an interdisciplinary thought-leader in leveraging AI/ML algorithms, text/audio/image/video big data ...
https://cis.temple.edu/~latecki/Papers/OSB_ICDM07.pdf
The proposed OSB computes the distance value between two sequences based directly on the distances of corre-sponding elements, just as DTW does, and it allows the ignoring of outlier points on both the query and target se-quences to find the best match, just as LCSS does. The main difference between DTW and OSB is that, unlike DTW, OSB can skip outlier elements of the query and target se ...
https://scholarshare.temple.edu/server/api/core/bitstreams/d5d8ff3d-a246-44fa-ba1a-7ed48b4e6adf/content
Professor of Law, Temple University, Beasley School of Law. The author thanks Temple University, Beasley School of Law for research support, and Kristen Tiscione, Kirsten Davis, and Kristen Murray for the discussions and feedback that inspired this article. Many thanks also to Megan Albright and Emily Kowey for their able research assistance.
https://cis.temple.edu/~latecki/Papers/GIFT-IEEEMM2017.pdf
Abstract—Projective analysis is an important solution in three-dimensional (3D) shape retrieval, since human visual perceptions of 3D shapes rely on various 2D observations from different viewpoints. Although multiple informative and discriminative views are utilized, most projection-based retrieval systems suffer from heavy computational cost, and thus cannot satisfy the basic requirement ...