https://cis.temple.edu/~latecki/Courses/AI-Fall12/Lectures/ParameterEstimation.pdf
Parameter Estimation in Probabilistic Models, Linear Regression and Logistic Regression Piyush Rai
https://law.temple.edu/wp-content/uploads/Cognitive-Bias-and-Its-Impact-on-Expert-Witnesses-and-the-Court.pdf
Expert evidence provides a much needed contribution to the courts in administering justice. Understanding the way humans think and how the brain processes information offers insights to circumstances in which even expert evidence may be influenced by contextual information and cognitive bias. Cognitive science can identify such potential weaknesses and suggest practical ways to mitigate them.
https://cis.temple.edu/~pwang/AGI-Curriculum.html
Suggested Education for Future AGI Researchers The following list is a partial education plan for students interested in the research of Artificial General Intelligence. Notes: The opinions expressed here are highly personal. Not only are the topics and reading materials selected according to my opinion, but also there are my own works included (they are distinguished from the others using ...
https://cis.temple.edu/~jiewu/
Jie Wu, Ph.D., Fellow of AAAS, and Fellow of IEEE
https://teaching.temple.edu/sites/teaching/files/resource/pdf/1%20Bloom%27s%20Taxonomy%20Blooms%20Digitally%20_%20Tech%20Learning.pdf
Bloom's Revised Taxonomy In the 1990's, a former student of Bloom, Lorin Anderson, revised Bloom's Taxonomy and published this-Bloom's Revised Taxonomy in 2001.Key to this is the use of verbs rather than nouns for each of the categories and a rearrangement of the sequence within the taxonomy. They are arranged below in increasing order, from low to high.
https://ronlevygroup.cst.temple.edu/courses/2020_fall/chem5302/lectures/chem5302_lecture2.pdf
Canonical Ensemble: An ensemble with the same Number of molecules, Volume and Temperature, but different Energy per system. (N, V, T)
https://cis-linux1.temple.edu/~jiewu/research/publications/Publication_files/ICPADS2024.pdf
Abstract—Federated Learning (FL) is an emerging privacy-preserving distributed machine learning paradigm that enables numerous clients to collaboratively train a global model without transmitting private datasets to the FL server. Unlike most existing research, this paper introduces a Data-Driven FL system in Unmanned Aerial Vehicle (UAV) networks, named DDFL, which features an innovative ...
https://cis.temple.edu/~jiewu/research/publications/Publication_files/ICDE2024_Online_Federated_Learning_on_Distributed_Unknown_Data_Using_UAVs.pdf
Abstract—Along with the advance of low-altitude economy, a variety of applications based on Unmanned Aerial Vehicles (UAVs) have been developed to accomplish diverse tasks. In this paper, we focus on the scenario of multiple UAVs performing Federated Learning (FL) tasks. Specifically, a group of UAVs is scheduled to repeatedly visit some Points of Interest (PoIs), collect the data produced ...
https://law.temple.edu/aer/publication/duped-why-innocent-people-confess-and-why-we-believe-their-confessions/
July 10, 2023In 1992, Willie Veasy confessed to a murder, a confession a jury accepted despite a time card showing him to have been at work as a dishwasher 8 miles away. In 2001, Jermel Lewis signed a confession admitting to participating in Philadelphia’s worst mass killing – the seven homicides in what was known
https://cis.temple.edu/~latecki/Courses/CIS2033-Spring12/ElementaryProbabilityforApplications/ch2.pdf
The events Ai,j that persons i and j have the same birthday are only pairwise independent, so strictly speaking (2.12) does not apply. However it gives a reasonable approximation. The number of pairs of people is C25,2 = 300 while the probability of a match for a given pair is 1/365, so by (2.13) the probability of no match is