Zobrazeno 1 - 10
of 298
pro vyhledávání: '"Ramakrishnan, Raghu"'
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:
Aguilar-Saborit, Josep, Ramakrishnan, Raghu, Bocksrocker, Kevin, Halverson, Alan, Kosinsky, Konstantin, O'Connor, Ryan, Poliakova, Nadejda, Shafiei, Moe, Kim, Taewoo, Kon-Kim, Phil, Mahmud-Ansari, Haris, Matuszyk, Blazej, Miles, Matt, Mohanan, Sumin, Petculescu, Cristian, Rahesh-Madan, Ishan, Rose-Wirshing, Emma, Yousefi, Elias
In Polaris, we introduced a cloud-native distributed query processor to perform analytics at scale. In this paper, we extend the underlying Polaris distributed computation framework, which can be thought of as a read-only transaction engine, to execu
Externí odkaz:
http://arxiv.org/abs/2401.11162
The advent of Foundation Models is transforming machine learning across many modalities (e.g., language, images, videos) with prompt engineering replacing training in many settings. Recent work on tabular data (e.g., TabPFN) hints at a similar opport
Externí odkaz:
http://arxiv.org/abs/2312.08598
Autor:
Camacho-Rodríguez, Jesús, Agrawal, Ashvin, Gruenheid, Anja, Gosalia, Ashit, Petculescu, Cristian, Aguilar-Saborit, Josep, Floratou, Avrilia, Curino, Carlo, Ramakrishnan, Raghu
Publikováno v:
Proceedings of the ACM on Management of Data (2024) Volume 2 Issue 1
Data processing engines increasingly leverage distributed file systems for scalable, cost-effective storage. While the Apache Parquet columnar format has become a popular choice for data storage and retrieval, the immutability of Parquet files render
Externí odkaz:
http://arxiv.org/abs/2305.01120
Autor:
Psallidas, Fotis, Agrawal, Ashvin, Sugunan, Chandru, Ibrahim, Khaled, Karanasos, Konstantinos, Camacho-Rodríguez, Jesús, Floratou, Avrilia, Curino, Carlo, Ramakrishnan, Raghu
Provenance encodes information that connects datasets, their generation workflows, and associated metadata (e.g., who or when executed a query). As such, it is instrumental for a wide range of critical governance applications (e.g., observability and
Externí odkaz:
http://arxiv.org/abs/2210.14047
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:
Ramakrishnan, Raghu, Kaur, Arvinder
Publikováno v:
In Information and Software Technology July 2020 123
Autor:
Rosen, Joshua, Polyzotis, Neoklis, Borkar, Vinayak, Bu, Yingyi, Carey, Michael J., Weimer, Markus, Condie, Tyson, Ramakrishnan, Raghu
Large datasets ("Big Data") are becoming ubiquitous because the potential value in deriving insights from data, across a wide range of business and scientific applications, is increasingly recognized. In particular, machine learning - one of the foun
Externí odkaz:
http://arxiv.org/abs/1303.3517
Autor:
Ramakrishnan, Raghu, Kaur, Arvinder
Publikováno v:
In Information and Software Technology April 2019 108:88-98