https://cis.temple.edu/tagit/presentations/Hopfield%20Networks%20is%20all%20you%20need.pdf
Classical Binary Hopfield Networks More complicated, patterns like (binary) images can be learned.
https://bulletin.temple.edu/graduate/scd/cst/bioinformatics-biological-data-science-psm/
About the Program Bioinformatics and Biological Data Science are the disciplines of science wherein computers are joined with the latest discoveries in genomics, biochemistry and biophysics. These rapidly growing fields bring together elements of biology, chemistry, computer science, physics and statistics. The Bioinformatics and Biological Data Science degree at Temple University, a leader in ...
https://cis.temple.edu/~latecki/Courses/AI-Fall12/Lectures/RandomFields_Sarah.pdf
C. Sutton and A. McCallum, An Introduction to Conditional Random Fields for Relational Learning, MIT Press, 2006. D. Precup, Graphical Models, Probabilistic Reasoning in AI, McGill University, 2008. J. Cao and K.J. Worsley, Applications of Random Fields in Human Brain Mapping, American Mathematical Society, 1991.
https://sites.temple.edu/wise2022/files/2022/11/WISE-2022-Schedule-and-Program-11.24.22.pdf
December 14-16, 2022, Copenhagen Business School, Denmark Preliminary – Subject to Change
https://cis.temple.edu/~jiewu/research/publications/Publication_files/WENJUNJIANG2021TWeb.pdf
In online systems, including e-commerce platforms, many users resort to the reviews or comments generated by previous consumers for decision making, while their time is limited to deal with many reviews. Therefore, a review summary, which contains all important features in user-generated reviews, is expected. In this paper, we study “how to generate a comprehensive review summary from a ...
https://cis.temple.edu/~jiewu/research/publications/Publication_files/DiVE.pdf
Abstract—Ensuring stable and high-quality real-time video an-alytics for computationally constrained mobile agents is essential. However, limited computing resources and network bandwidth present significant challenges in meeting the objective of low response time and high inference accuracy. In this paper, we present DiVE, an edge-assisted video analytics system that utilizes motion vectors ...
https://cis.temple.edu/~pwang/Publication/AI_Misconceptions.pdf
In the discussions on the limitation of Artificial Intelligence (AI), there are three major misconceptions, which identify an AI system with an ax-iomatic system, a Turing machine, and a system with a model-theoretic se-mantics, respectively. Though these three notions can be used to describe a computer system for certain purposes, they are not always the proper theoretical notions when an AI ...
https://www.fox.temple.edu/sites/fox/files/Frontiers-Machines-versus-Humans-The-Impact-of-Artificial-Intelligence-Chatbot-Disclosure-on-Customer-Purchases.pdf
Frontiers: Machines vs. Humans: The Impact of Artificial Intelligence Chatbot Disclosure on Customer Purchases Xueming Luo,aSiliang Tong,aZheng Fang,bZhe Quc
https://cis.temple.edu/~latecki/Courses/CIS2166-Fall16/Lectures/MatrixAlg1.pdf
A matrix is a rectangular array of numbers or other mathematical objects, for which operations such as addition and multiplication are defined. Most of this article focuses on real matrices, i.e., matrices whose elements are real numbers. For instance, this is a real matrix: The numbers, symbols or expressions in the matrix are called its entries or its elements. The horizontal and vertical ...
https://cis.temple.edu/~ingargio/cis587/readings/id3-c45.html
Introduction ID3 and C4.5 are algorithms introduced by Quinlan for inducing Classification Models, also called Decision Trees, from data.