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An Asynchronous Advantage Actor-Critic Reinforcement Learning Method for Stock Selection and Portfolio Management

Published in Proceedings of the 2nd International Conference on Big Data Research, 2018

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Recommended citation: Qinma Kang, Huizhuo Zhou, Yunfan Kang (2018). "An Asynchronous Advantage Actor-Critic Reinforcement Learning Method for Stock Selection and Portfolio Management." Proceedings of the 2nd International Conference on Big Data Research, pp. 141-145.
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Scalable Multi-resolution Spatial Visualization for Anthropogenic Litter Data

Published in Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2019

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Recommended citation: Yunfan Kang, Ziang Zhao, Amr Magdy, Win Cowger, Andrew Gray (2019). "Scalable Multi-resolution Spatial Visualization for Anthropogenic Litter Data." Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, pp. 560-563.
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Trash Taxonomy Tool: harmonizing classification systems used to describe trash in environments

Published in Microplastics and Nanoplastics, 2022

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Recommended citation: Hannah Hapich, Win Cowger, Andrew Gray, Neil Tangri, Tony Hale, Amr Magdy, Antoinette Vermilye, Walter Yu, Dick Ayres, Charles Moore, John Vermilye, Samiksha Singh, Aaron N. K. Haiman, Kathryn Youngblood, Yunfan Kang, Margaret McCauley, Trevor Lok, Shelly Moore, Eric Baggs, Sherry Lippiatt, Peter Kohler, Gary Conley, Janna Taing, Jeremiah Mock (2022). "Trash Taxonomy Tool: harmonizing classification systems used to describe trash in environments." Microplastics and Nanoplastics, 2(1).
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Scalable and Expressive Spatial Analysis and Modeling

Published in PhD Dissertation, University of California, Riverside, 2023

Recommended citation: Yunfan Kang (2023). "Scalable and Expressive Spatial Analysis and Modeling." PhD Dissertation, University of California, Riverside.

Scalable Evaluation of Local K-Function for Radius-Accurate Hotspot Detection in Spatial Networks

Published in Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems, 2023

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Recommended citation: Yongyi Liu, Yunfan Kang, Ahmed Mahmood, Amr Magdy (2023). "Scalable Evaluation of Local K-Function for Radius-Accurate Hotspot Detection in Spatial Networks." Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems, pp. 1-12.
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A Convergence Framework for Integrating CyberGIS Education and Research on I-GUIDE Platform

Published in I-GUIDE Forum 2024: Convergence Science and Geospatial AI for Environmental Sustainability, 2024

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Recommended citation: Fangzheng Lyu, Furqan Baig, Yunfan Kang, Erick Li, Anand Padmanabhan, Shaowen Wang (2024). "A Convergence Framework for Integrating CyberGIS Education and Research on I-GUIDE Platform." I-GUIDE Forum 2024: Convergence Science and Geospatial AI for Environmental Sustainability.
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Pyneapple-L: Scalable Expressive Learning-based Spatial Analysis

Published in Proceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems, 2024

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Recommended citation: Yongyi Liu, Nicolas Lee, Yunfan Kang, Mohammad Reza Shahneh, Ahmed Mahmood, Vishal Rohith Chinnam, Aparna Vivek Sarawadekar, Samet Oymak, Ibrahim Sabek, Amr Magdy (2024). "Pyneapple-L: Scalable Expressive Learning-based Spatial Analysis." Proceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems, pp. 645-648.
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I-GUIDE Platform for Geospatial Data-intensive Convergence Research and Education

Published in Practice and Experience in Advanced Research Computing 2025: The Power of Collaboration, 2025

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Recommended citation: Shaowen Wang, Furqan Baig, Yunfan Kang, Erick Li, Alexander Michels, Nattapon Jaroenchai, Anand Padmanabhan, Arunesh Kumar, Rajesh Kalyanam, Noah S. Oller Smith, X. Carol Song, Lan Zhao, Steven Manson, Mohan Ramamurthy, Sina Taghavikish, David Tarboton (2025). "I-GUIDE Platform for Geospatial Data-intensive Convergence Research and Education." Practice and Experience in Advanced Research Computing 2025: The Power of Collaboration, pp. 1-5.
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