https://sites.temple.edu/subodha/2017/08/23/journal-publications/
Y. Ji, S. Kumar, and S.P. Sethi, “Needle Exchange for Controlling HIV Spread Under Endogenous Infectivity,” INFOR: Information Systems and Operational Research, Vol. 55, No. 2, 2017, pp. 93-117.
https://sites.temple.edu/subodha/files/2025/04/Subodha-CV-Web.pdf
93. “GIANT grocery store goes green by electrifying fleets,” NBC 10 Philadelphia News, April 22, 2023. • The entire package was broadcast as an NBC10 special called "Climate in Crisis: How Philly Is Building Towards a Sustainable Future." 94. “Google needs to ramp up AI-powered search to keep Samsung,” TechTarget, April 20, 2023. 95.
https://cis.temple.edu/~pwang/papers.html
Insufficient knowledge and resources: a biological constraint and its functional implications [Papers from AAAI 2009 Fall Symposium on Biologically Inspired Cognitive Architectures, Pages 88-93, Arlington, Virginia, November 2009. An extended version is published as a journal article in 2011.]
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https://cis.temple.edu/~pwang/NARS-Intro.html
Intelligence: From Definition to Design, Proceedings of the Third International Workshop on Self-Supervised Learning, PMLR 192:35-47, 2022 From NARS to a thinking machine, Advance of Artificial General Intelligence, Pages 75-93, IOS Press, Amsterdam, 2007 Comprehensive descriptions:
https://www.fox.temple.edu/sites/fox/files/documents/CVs/xueming-luo-cv.pdf
Luo, Xueming and Naveen Donthu (2002), "Advertising Maybe Inefficient Irrespective of How the Advertising Budget Was Set," Journal of Advertising Research, 42 (2), 93-95.
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https://liberalarts.temple.edu/directory/lauren-alloy
A prospective test of three hypotheses. Clinical Psychological Science, 7, 93-109. Ng, T.H., Alloy, L.B., & Smith, D.V. (2019). Meta-analysis of reward processing in major depressive disorder reveals distinct abnormalities within the reward circuit. Translational Psychiatry, 9: 293. https://doi.org/10.1038/s41398-019-0644-x
https://cis.temple.edu/~jiewu/research/publications/Publication_files/jiang_www_2020.pdf
on MovieLens-1m and by 59.93% on Amazon-Kindle-Store when the top 10 items are recommended. It demonstrates that a compre-hensive preference representation could promote recommendation system to gain a better understand of users’ behavioral patterns, which is also raised in [37].
https://cis.temple.edu/~wu/research/publications/Publication_files/1571039973-LCN2024.pdf
Subsequently, with the inclusion of 10 samples (k = 10), the model exhibits a notable increase in accuracy to 93%, which significantly exceeds the baseline ac-curacy of 62%.