https://cis.temple.edu/~wu/teaching/Spring%202015/EGWY04.pdf
Abstract—In this paper we provide a theoretical foundation for the problem of network localization in which some nodes know their locations and other nodes determine their locations by measuring the distances to their neighbors. We construct grounded graphs to model network localization and apply graph rigidity theory to test the conditions for unique localizability and to construct uniquely ...
https://www.fox.temple.edu/academics/graduate-programs/specialized-masters
Master the science of risk in finance and insurance with a specialized advanced degree. Learn the analytic options for bankers, consultants, government regulators, insurers, and policymakers required for professional credentials in actuarial science through the 10-course curriculum.
https://cis.temple.edu/~friedman/cis071/Lecture4-web.doc
The book also uses flow charts, which are sometimes handy for visualizing what is going on with a decision structure. However, pseudo-code, if properly indented and written with a little care is a preferred mechanism for mapping out the logic of a decision before trying to program it (and having to worry about syntax).
https://cis.temple.edu/~jiewu/research/publications/Publication_files/m48122-zhao%20final.pdf
ArrayPipe: Introducing Job-Array Pipeline Parallelism for High Throughput Model Exploration Hairui Zhao1, Hongliang Li1,2,∗, Qi Tian1, Jie Wu3, Meng Zhang1, Xiang Li1, Haixiao Xu4
https://law.temple.edu/admissions/graduate-llm/
Temple University Beasley School of Law 1719 North Broad Street Philadelphia, PA 19122 (215) 204-7861
https://cis.temple.edu/~latecki/Courses/AI-Fall11/Lectures/ch7EL.ppt
Data1 Data2 … Data m Learner1 = Learner2 = … = Learner m Different methods for changing training data: Bagging: Resample training data Boosting: Reweight training data Bagging Bagging Create ensembles by “bootstrap aggregation”, i.e., repeatedly randomly resampling the training data (Brieman, 1996).
https://cis.temple.edu/~latecki/Papers/ICME2024.pdf
Abstract—Camouflaged object detection (COD) is a challeng-ing task that identifies camouflaged objects from highly similar backgrounds. Existing methods typically treat the whole object equally while neglecting the indistinguishable regions that require more attention than other regions. In this paper, we propose a Fuzzy Boundary-Guided Network (FBG-Net) for camouflaged object detection ...
https://cis.temple.edu/~latecki/Courses/CIS2033-Spring13/Modern_intro_probability_statistics_Dekking05.pdf
A modern introduction to probability and statistics. — (Springer texts in statistics) 1. Probabilities 2. Mathematical statistics I. Dekking, F. M.
https://www.fox.temple.edu/news/2018/03/stanley-franny-wang-make-2-million-gift-fox-school-business
A $2 million gift from Temple University graduates Stanley and Franny Wang will support a fully endowed chair professorship at the Fox School of Business. The couple’s philanthropic support allows the Fox School to create an endowed fund for the Stanley and Franny Wang Chair in Business and Management. This fully endowed chair will be held by a leading scholar in a department soon to be ...
https://cis.temple.edu/~giorgio/old/cis307s96/readings/pthreads.html
CIS 307: Measuring Time, Pthreads , , Measuring Time Measuring time on the computer is non trivial. Here are some of the things we may want to do with time. Determine the current time Specify the amount of time we are ready to wait, or sleep To determine the time it takes to execute some commands and programs. In all these cases we have a problem of Precision and of Accuracy. By Precision we ...