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.
https://cis.temple.edu/~latecki/Papers/JoPanECAI2024.pdf
Addressing these gaps, we introduce the FlowLearn Dataset1, which includes both scientific and simulated flowcharts. The scien-tific subset features 3,858 flowcharts sourced from scientific liter-ature, annotated with captions (median length of 25 words) and in-figure text. The simulated subset consists of 10,000 flowcharts gener-ated from Mermaid code. This simulated subset enhances the ...
https://cis.temple.edu/~wangp/5603-AI/Project/2022S/pattersonblaker/Ward_Patterson_Final_Report.pdf
1 Abstract Minecraft has been the focus of much AI research in past years. Most recently, interest has risen in procedural generation of settlements in Minecraft, largely due to a annual competition established in 2018 called the Generative Design in Minecraft Competition. Inspired by this recent research, we aim to develop a set of algorithms that are capable of building a realistic ...
https://cis.temple.edu/~jiewu/research/publications/Publication_files/Privacy-Preserving_Federated_Neural_Architecture_Search_With_Enhanced_Robustness_for_Edge_Computing.pdf
Abstract—With the development of large-scale artificial intelli-gence services, edge devices are becoming essential providers of data and computing power. However, these edge devices are not immune to malicious attacks. Federated learning (FL), while pro-tecting privacy of decentralized data through secure aggregation, struggles to trace adversaries and lacks optimization for hetero-geneity ...
https://cis.temple.edu/~lakaemper/courses/cis350_2004/etc/moeller_triangle.pdf
1 Introduction Most collision detection algorithms, such as OBBTree [Gottschalk96], sphere hier-archies [Hubbard96] and BV-trees [Klosowski97], try to minimize the number of primitive-primitive intersections that have to be computed. Still, a fast and reliable method for computing the primitive-primitive intersection is desired. Since render-ing hardware is often targeted for triangles, the ...
https://cis.temple.edu/~latecki/Courses/CIS750-03/Papers/KalmanFilterSIGGRAPH2001.pdf
1. Introduction The Kalman filter is a mathematical power tool that is playing an increasingly important role in computer graphics as we include sensing of the real world in our systems. The good news is you don’t have to be a mathematical genius to understand and effectively use Kalman filters. This tutorial is designed to provide developers of graphical systems with a basic understanding ...
https://sites.temple.edu/ticlj/files/2017/02/30.1.Scharre-TICLJ.pdf
Paul Scharre* Much of the debate on autonomous weapons presumes a choice between human versus autonomous decision-making over targeting and engagement decisions. In fact, in many situations, human-machine teaming in engagement decisions will not only be possible but preferable. Hybrid human-machine cognitive architectures will be able to leverage the precision and reliability of automation ...
https://cis.temple.edu/~jiewu/research/publications/Publication_files/m37113-chen%20final.pdf
Abstract—Recent years have witnessed the unprecedented performance of convolutional networks in image super-resolution (SR). SR involves upscaling a single low-resolution image to meet application-specific image quality demands, making it vital for mobile devices. However, the excessive computational and memory requirements of SR tasks pose a challenge in mapping SR networks on a single ...
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 ...
https://cis.temple.edu/~jiewu/teaching/Spring%202013/01-savvides-localization-wireless-sensor-networks-fine-grained.pdf
Abstract— Wireless communication systems have become increasingly common because of advances in radio and embedded system technologies. In recent years, a new class of applications that networks these wireless de-vices together is evolving. A representative of this class that has received considerable attention from the research community is the wireless sensor network. Such a sensor ...