Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Krishnan, Subru"'
Autor:
Zhu, Yiwen, Tian, Yuanyuan, Cahoon, Joyce, Krishnan, Subru, Agarwal, Ankita, Alotaibi, Rana, Camacho-Rodríguez, Jesús, Chundatt, Bibin, Chung, Andrew, Dutta, Niharika, Fogarty, Andrew, Gruenheid, Anja, Haynes, Brandon, Interlandi, Matteo, Iyer, Minu, Jurgens, Nick, Khushalani, Sumeet, Kroth, Brian, Kumar, Manoj, Leeka, Jyoti, Matusevych, Sergiy, Mittal, Minni, Mueller, Andreas, Muthyala, Kartheek, Nagulapalli, Harsha, Park, Yoonjae, Patel, Hiren, Pavlenko, Anna, Poppe, Olga, Ravindran, Santhosh, Saur, Karla, Sen, Rathijit, Suh, Steve, Tarafdar, Arijit, Waghray, Kunal, Wang, Demin, Curino, Carlo, Ramakrishnan, Raghu
Modern cloud has turned data services into easily accessible commodities. With just a few clicks, users are now able to access a catalog of data processing systems for a wide range of tasks. However, the cloud brings in both complexity and opportunit
Externí odkaz:
http://arxiv.org/abs/2405.01813
Autor:
Cahoon, Joyce, Wang, Wenjing, Zhu, Yiwen, Lin, Katherine, Liu, Sean, Truong, Raymond, Singh, Neetu, Wan, Chengcheng, Ciortea, Alexandra M, Narasimhan, Sreraman, Krishnan, Subru
Publikováno v:
Proceedings of the VLDB Endowment 15 (12), 3509-3521, 2022
Selecting the optimal cloud target to migrate SQL estates from on-premises to the cloud remains a challenge. Current solutions are not only time-consuming and error-prone, requiring significant user input, but also fail to provide appropriate recomme
Externí odkaz:
http://arxiv.org/abs/2208.04978
Autor:
Zhu, Yiwen, Krishnan, Subru, Karanasos, Konstantinos, Tarte, Isha, Power, Conor, Modi, Abhishek, Kumar, Manoj, Zhang, Deli, Muthyala, Kartheek, Jurgens, Nick, Sakalanaga, Sarvesh, Darbha, Sudhir, Iyer, Minu, Agarwal, Ankita, Curino, Carlo
Microsoft's internal big-data infrastructure is one of the largest in the world -- with over 300k machines running billions of tasks from over 0.6M daily jobs. Operating this infrastructure is a costly and complex endeavor, and efficiency is paramoun
Externí odkaz:
http://arxiv.org/abs/2106.11445
Autor:
Namaki, Mohammad Hossein, Floratou, Avrilia, Psallidas, Fotis, Krishnan, Subru, Agrawal, Ashvin, Wu, Yinghui, Zhu, Yiwen, Weimer, Markus
There has recently been a lot of ongoing research in the areas of fairness, bias and explainability of machine learning (ML) models due to the self-evident or regulatory requirements of various ML applications. We make the following observation: All
Externí odkaz:
http://arxiv.org/abs/2001.01861
Autor:
Psallidas, Fotis, Zhu, Yiwen, Karlas, Bojan, Interlandi, Matteo, Floratou, Avrilia, Karanasos, Konstantinos, Wu, Wentao, Zhang, Ce, Krishnan, Subru, Curino, Carlo, Weimer, Markus
The recent success of machine learning (ML) has led to an explosive growth both in terms of new systems and algorithms built in industry and academia, and new applications built by an ever-growing community of data science (DS) practitioners. This qu
Externí odkaz:
http://arxiv.org/abs/1912.09536
Autor:
Karanasos, Konstantinos, Interlandi, Matteo, Xin, Doris, Psallidas, Fotis, Sen, Rathijit, Park, Kwanghyun, Popivanov, Ivan, Nakandal, Supun, Krishnan, Subru, Weimer, Markus, Yu, Yuan, Ramakrishnan, Raghu, Curino, Carlo
The broadening adoption of machine learning in the enterprise is increasing the pressure for strict governance and cost-effective performance, in particular for the common and consequential steps of model storage and inference. The RDBMS provides a n
Externí odkaz:
http://arxiv.org/abs/1911.00231
Autor:
Agrawal, Ashvin, Chatterjee, Rony, Curino, Carlo, Floratou, Avrilia, Gowdal, Neha, Interlandi, Matteo, Jindal, Alekh, Karanasos, Kostantinos, Krishnan, Subru, Kroth, Brian, Leeka, Jyoti, Park, Kwanghyun, Patel, Hiren, Poppe, Olga, Psallidas, Fotis, Ramakrishnan, Raghu, Roy, Abhishek, Saur, Karla, Sen, Rathijit, Weimer, Markus, Wright, Travis, Zhu, Yiwen
Machine learning (ML) has proven itself in high-value web applications such as search ranking and is emerging as a powerful tool in a much broader range of enterprise scenarios including voice recognition and conversational understanding for customer
Externí odkaz:
http://arxiv.org/abs/1909.00084
Autor:
Shao, Liqun, Zhu, Yiwen, Eswaran, Abhiram, Lieber, Kristin, Mahajan, Janhavi, Thigpen, Minsoo, Darbha, Sudhir, Liu, Siqi, Krishnan, Subru, Srinivasan, Soundar, Curino, Carlo, Karanasos, Konstantinos
Microsoft's internal big data analytics platform is comprised of hundreds of thousands of machines, serving over half a million jobs daily, from thousands of users. The majority of these jobs are recurring and are crucial for the company's operation.
Externí odkaz:
http://arxiv.org/abs/1908.09048
Akademický článek
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Autor:
Cahoon, Joyce, Wang, Wenjing, Zhu, Yiwen, Lin, Katherine, Liu, Sean, Truong, Raymond, Singh, Neetu, Wan, Chengcheng, Ciortea, Alexandra M, Narasimhan, Sreraman, Krishnan, Subru
Publikováno v:
Proceedings of the VLDB Endowment. 15:3509-3521
Selecting the optimal cloud target to migrate SQL estates from on-premises to the cloud remains a challenge. Current solutions are not only time-consuming and error-prone, requiring significant user input, but also fail to provide appropriate recomme
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::61a9377092aec1817110e82aa1ac7694
https://doi.org/10.14778/3554821.3554840
https://doi.org/10.14778/3554821.3554840
