Zobrazeno 1 - 10
of 323
pro vyhledávání: '"Malik, Sana"'
Autor:
Malik, Sana, Akram, Faiza, Ali, Muhammad, Javed, Mohsin, Mateen, Rana Muhammad, Zidan, Ammar, Bahadur, Ali, Iqbal, Shahid, Mahmood, Sajid, Farouk, Abd-ElAziem, Aloufi, Salman
Publikováno v:
In Journal of Molecular Structure 25 February 2025 1323
Autor:
Zeng, Zehua, Moh, Phoebe, Du, Fan, Hoffswell, Jane, Lee, Tak Yeon, Malik, Sana, Koh, Eunyee, Battle, Leilani
Although we have seen a proliferation of algorithms for recommending visualizations, these algorithms are rarely compared with one another, making it difficult to ascertain which algorithm is best for a given visual analysis scenario. Though several
Externí odkaz:
http://arxiv.org/abs/2109.02706
Autor:
Usman, Muhammad, Khan, Aqib Zafar, Malik, Sana, Xiong, Wenlong, Lv, Yongkun, Zhang, Shen, Zhao, Anqi, Solovchenko, A.E., Alam, Md Asraful, Alessa, Abdulrahman H., Mehmood, Muhammad Aamer, Xu, Jingliang
Publikováno v:
In Chemosphere August 2024 361
Autor:
Mehmood, Muhammad Aamer, Amin, Mahwish, Haq, Muhammad Adnan Ul, Shahid, Ayesha, Malik, Sana, Siddiqui, Amna Jabbar, Wang, Ning, Zhu, Hui, Rasul, Azhar, Chaudhry, Ahmed Hassan, Nadeem, Khalid, Boopathy, Raj, Zaman, Qamar Uz, Musharraf, Syed Ghulam
Publikováno v:
In Bioresource Technology Reports June 2024 26
Autor:
Harris, Camille, Rossi, Ryan A., Malik, Sana, Hoffswell, Jane, Du, Fan, Lee, Tak Yeon, Koh, Eunyee, Zhao, Handong
Visualization recommendation systems simplify exploratory data analysis (EDA) and make understanding data more accessible to users of all skill levels by automatically generating visualizations for users to explore. However, most existing visualizati
Externí odkaz:
http://arxiv.org/abs/2103.11297
Autor:
Qian, Xin, Rossi, Ryan A., Du, Fan, Kim, Sungchul, Koh, Eunyee, Malik, Sana, Lee, Tak Yeon, Ahmed, Nesreen K.
Visualization recommendation work has focused solely on scoring visualizations based on the underlying dataset and not the actual user and their past visualization feedback. These systems recommend the same visualizations for every user, despite that
Externí odkaz:
http://arxiv.org/abs/2102.06343
Autor:
Qian, Xin, Rossi, Ryan A., Du, Fan, Kim, Sungchul, Koh, Eunyee, Malik, Sana, Lee, Tak Yeon, Chan, Joel
Visualization recommendation seeks to generate, score, and recommend to users useful visualizations automatically, and are fundamentally important for exploring and gaining insights into a new or existing dataset quickly. In this work, we propose the
Externí odkaz:
http://arxiv.org/abs/2009.12316
While decision makers have begun to employ machine learning, machine learning models may make predictions that bias against certain demographic groups. Semi-automated bias detection tools often present reports of automatically-detected biases using a
Externí odkaz:
http://arxiv.org/abs/2004.12388
Machine learning models often make predictions that bias against certain subgroups of input data. When undetected, machine learning biases can constitute significant financial and ethical implications. Semi-automated tools that involve humans in the
Externí odkaz:
http://arxiv.org/abs/2003.07680