https://sites.temple.edu/edvice/2021/11/24/learning-preferences-are-not-learning-styles-and-why-the-language-we-use-matters/
Claudia J. Stanny, Ph.D. Let’s begin with debunking a persistent misconception about learning: Learning styles do not exist. Moreover, matching instruction strategies to a particular learning style, such as using visuals to teach a “visual learner,” does not improve learning for that particular student (Pashler, McDaniel, Roher, & Bjork, 2009). Worse, using the wrong sensory modality for ...
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://liberalarts.temple.edu/academics/departments-and-programs/geography-environment-and-urban-studies/graduate
Join an innovative program that integrates the contributions of several areas related to geography and urban studies. Hone skills for designing and teaching curricula in college and postgraduate environments, as well as preparing for high-level social research.
https://sites.temple.edu/ticlj/files/2017/05/31.1_Dunoff_Article-19.pdf
―the common man.‖ For example, in his July 1948 acceptance speech of the Progressive Party‘s nomination for President, Wallace declared his commitment to ―using the power of our democracy to control rigorously the power of huge corporate monopolies and international big business,‖ and stated that he was ―committed to using the power and prestige of the United States to help the ...
https://cis.temple.edu/~latecki/Papers/ChamferECCVFinal.pdf
2 Related work There is a large number of applications of chamfer matching in computer vision and in medical image analysis. Chamfer distance was first introduced by Barrow et al. [2] in 1977 with a goal of matching two collections of contour fragments. Until today chamfer matching is widely used in object detection and classifica-tion task due to its tolerance to misalignment in position ...
https://secretary.temple.edu/sites/secretary/files/policies/03.70.12.pdf
Temple University Student Government has adopted a unity statement that reflects the values of the diverse Temple community, by which all students are expected to abide. “As Temple Owls, we respect all members of our university and local community regardless of: race, ethnicity, sex, gender, identity, sexual orientation, age, religion, socioeconomic status, veteran status, political ...
https://news.temple.edu/news/2022-12-06/understanding-america-relationship-firearms
Experts on gun violence from Temple University explain the origins of America’s gun violence crisis and propose solutions to put an end to the epidemic.
https://sites.temple.edu/nickerson/files/2017/07/Gerber_Green_Nickerson.PA_.2001.pdf
If the publication decisions of journals are a function of the statistical significance of re-search findings, the published literature may suffer from “publication bias.” This paper describes a method for detecting publication bias. We point out that to achieve statisti-cal significance, the effect size must be larger in small samples. If publications tend to be biased against ...
https://www.fox.temple.edu/sites/fox/files/documents/CVs/xueming-luo-cv.pdf
Bio: Xueming Luo is the Charles Gilliland Distinguished Chair Professor of Marketing, Professor of Strategy, and Professor of MIS, and Founder/ Director of the Global Institute for Artificial Intelligence & Business Analytics in the Fox School of Business at Temple University. He is an interdisciplinary thought-leader in leveraging AI/ML algorithms, text/audio/image/video big data ...
https://cis.temple.edu/~latecki/Papers/CIDM07.pdf
Abstract. Outlier detection has recently become an important problem in many industrial and financial applications. This problem is further complicated by the fact that in many cases, outliers have to be detected from data streams that arrive at an enormous pace. In this paper, an incremental LOF (Local Outlier Factor) algorithm, appropriate for detecting outliers in data streams, is proposed ...