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2020 – today
- 2024
[j6]Alexander van Renen, Dominik Horn, Pascal Pfeil, Kapil Vaidya, Wenjian Dong, Murali Narayanaswamy, Zhengchun Liu, Gaurav Saxena, Andreas Kipf, Tim Kraska:
Why TPC Is Not Enough: An Analysis of the Amazon Redshift Fleet. Proc. VLDB Endow. 17(11): 3694-3706 (2024)- [c3]Vikramank Y. Singh, Kapil Vaidya, Vinayshekhar Bannihatti Kumar, Sopan Khosla, Balakrishnan Narayanaswamy, Rashmi Gangadharaiah, Tim Kraska:
Panda: Performance Debugging for Databases using LLM Agents. CIDR 2024 - 2023
- [b1]Kapil Vaidya:
Instance-Optimized Data Structures for Membership Queries. MIT, USA, 2023 - 2022
- [j5]Kapil Vaidya, Tim Kraska, Subarna Chatterjee, Eric R. Knorr, Michael Mitzenmacher, Stratos Idreos:
SNARF: A Learning-Enhanced Range Filter. Proc. VLDB Endow. 15(8): 1632-1644 (2022) - [j4]Jialin Ding, Ryan Marcus, Andreas Kipf, Vikram Nathan, Aniruddha Nrusimha, Kapil Vaidya, Alexander van Renen, Tim Kraska:
SageDB: An Instance-Optimized Data Analytics System. Proc. VLDB Endow. 15(13): 4062-4078 (2022) - [j3]Ibrahim Sabek
, Kapil Vaidya, Dominik Horn, Andreas Kipf, Michael Mitzenmacher, Tim Kraska:
Can Learned Models Replace Hash Functions? Proc. VLDB Endow. 16(3): 532-545 (2022) - 2021
- [j2]Kapil Vaidya, Anshuman Dutt, Vivek R. Narasayya, Surajit Chaudhuri:
Leveraging Query Logs and Machine Learning for Parametric Query Optimization. Proc. VLDB Endow. 15(3): 401-413 (2021) - [c2]Kapil Vaidya, Eric Knorr, Michael Mitzenmacher, Tim Kraska:
Partitioned Learned Bloom Filters. ICLR 2021 - [i5]Ibrahim Sabek, Kapil Vaidya, Dominik Horn, Andreas Kipf, Tim Kraska:
When Are Learned Models Better Than Hash Functions? CoRR abs/2107.01464 (2021) - [i4]Ani Kristo, Kapil Vaidya, Tim Kraska:
Defeating duplicates: A re-design of the LearnedSort algorithm. CoRR abs/2107.03290 (2021) - [i3]Benjamin Spector, Andreas Kipf, Kapil Vaidya, Chi Wang, Umar Farooq Minhas, Tim Kraska:
Bounding the Last Mile: Efficient Learned String Indexing. CoRR abs/2111.14905 (2021) - 2020
- [c1]Ani Kristo, Kapil Vaidya, Ugur Çetintemel, Sanchit Misra, Tim Kraska:
The Case for a Learned Sorting Algorithm. SIGMOD Conference 2020: 1001-1016 - [i2]Kapil Vaidya, Eric Knorr, Tim Kraska, Michael Mitzenmacher:
Partitioned Learned Bloom Filter. CoRR abs/2006.03176 (2020)
2010 – 2019
- 2018
- [j1]Marek Chalupa, Krishnendu Chatterjee, Andreas Pavlogiannis, Nishant Sinha, Kapil Vaidya:
Data-centric dynamic partial order reduction. Proc. ACM Program. Lang. 2(POPL): 31:1-31:30 (2018) - 2016
- [i1]Krishnendu Chatterjee, Andreas Pavlogiannis, Nishant Sinha, Kapil Vaidya:
Data-centric Dynamic Partial Order Reduction. CoRR abs/1610.01188 (2016)
Coauthor Index
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