https://cis-linux1.temple.edu/~tug29203/25fall-2033/lectures/ch2.pdf
We choose r objects in succession from a population (set) of n distinct objects fa1; a1; ; ang, in such a way that after choosing each object and recording the choice, we return the object to the set before making the next choice.
https://cis.temple.edu/~giorgio/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.
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://www.fox.temple.edu/sites/fox/files/Complementarity-and-Cannibalization-of-Offline-to-Online-Targeting-A-Field-Experiment-on-Omnichannel-Commerce.pdf
However, it is debatable whether such offline-to-online tar-geting is effective. On the one hand, advocates argue that inducing offline customers to buy online may complement a firm’s store channel. This is because as more channels are used to engage customers, the value of these customers increases (Gimpel et al. 2018), and multichannel shoppers are more loyal and spend more than single ...
https://cis.temple.edu/~jiewu/research/publications/Publication_files/ICC2024.pdf
Abstract—Most intrusion detection systems (IDS) are vul-nerable to novel attacks and struggle to maintain a balance between high accuracy and a low false positive rate. Furthermore, the relevant features of Distributed Denial of Service (DDoS) attacks in conventional networks may not necessarily apply to the Software-defined network (SDN) environment. Additionally, weak feature selection ...