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Tim Kraska
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Publications
- 2023
- [j63]Ziniu Wu, Parimarjan Negi, Mohammad Alizadeh, Tim Kraska, Samuel Madden:
FactorJoin: A New Cardinality Estimation Framework for Join Queries. Proc. ACM Manag. Data 1(1): 41:1-41:27 (2023) - [j62]Parimarjan Negi, Ziniu Wu, Andreas Kipf, Nesime Tatbul, Ryan Marcus, Sam Madden, Tim Kraska, Mohammad Alizadeh:
Robust Query Driven Cardinality Estimation under Changing Workloads. Proc. VLDB Endow. 16(6): 1520-1533 (2023) - [c95]Parimarjan Negi, Laurent Bindschaedler, Mohammad Alizadeh, Tim Kraska, Jyoti Leeka, Anja Gruenheid, Matteo Interlandi:
Unshackling Database Benchmarking from Synthetic Workloads. ICDE 2023: 3659-3662 - 2022
- [j52]Ryan Marcus, Parimarjan Negi, Hongzi Mao, Nesime Tatbul, Mohammad Alizadeh, Tim Kraska:
Bao: Making Learned Query Optimization Practical. SIGMOD Rec. 51(1): 6-13 (2022) - [i61]Ziniu Wu, Parimarjan Negi, Mohammad Alizadeh, Tim Kraska, Samuel Madden:
FactorJoin: A New Cardinality Estimation Framework for Join Queries. CoRR abs/2212.05526 (2022) - 2021
- [j50]Parimarjan Negi, Ryan Marcus, Andreas Kipf, Hongzi Mao, Nesime Tatbul, Tim Kraska, Mohammad Alizadeh:
Flow-Loss: Learning Cardinality Estimates That Matter. Proc. VLDB Endow. 14(11): 2019-2032 (2021) - [c82]Ryan Marcus, Parimarjan Negi, Hongzi Mao, Nesime Tatbul, Mohammad Alizadeh, Tim Kraska:
Bao: Making Learned Query Optimization Practical. SIGMOD Conference 2021: 1275-1288 - [c80]Parimarjan Negi, Matteo Interlandi, Ryan Marcus, Mohammad Alizadeh, Tim Kraska, Marc T. Friedman, Alekh Jindal:
Steering Query Optimizers: A Practical Take on Big Data Workloads. SIGMOD Conference 2021: 2557-2569 - [i60]Parimarjan Negi, Ryan Marcus, Andreas Kipf, Hongzi Mao, Nesime Tatbul, Tim Kraska, Mohammad Alizadeh:
Flow-Loss: Learning Cardinality Estimates That Matter. CoRR abs/2101.04964 (2021) - [i59]Songtao He, Favyen Bastani, Mohammad Alizadeh, Hari Balakrishnan, Michael J. Cafarella, Tim Kraska, Sam Madden:
TagMe: GPS-Assisted Automatic Object Annotation in Videos. CoRR abs/2103.13428 (2021) - 2020
- [j43]Jialin Ding, Vikram Nathan, Mohammad Alizadeh, Tim Kraska:
Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads. Proc. VLDB Endow. 14(2): 74-86 (2020) - [c75]Parimarjan Negi, Ryan Marcus, Hongzi Mao, Nesime Tatbul, Tim Kraska, Mohammad Alizadeh:
Cost-Guided Cardinality Estimation: Focus Where it Matters. ICDE Workshops 2020: 154-157 - [c73]Songtao He, Favyen Bastani, Arjun Balasingam, Karthik Gopalakrishnan, Ziwen Jiang, Mohammad Alizadeh, Hari Balakrishnan, Michael J. Cafarella, Tim Kraska, Sam Madden:
BeeCluster: drone orchestration via predictive optimization. MobiSys 2020: 299-311 - [c72]Lujing Cen, Ryan Marcus, Hongzi Mao, Justin Gottschlich, Mohammad Alizadeh, Tim Kraska:
Learned garbage collection. MAPL@PLDI 2020: 38-44 - [c67]Vikram Nathan, Jialin Ding, Mohammad Alizadeh, Tim Kraska:
Learning Multi-Dimensional Indexes. SIGMOD Conference 2020: 985-1000 - [c64]Favyen Bastani, Songtao He, Arjun Balasingam, Karthik Gopalakrishnan, Mohammad Alizadeh, Hari Balakrishnan, Michael J. Cafarella, Tim Kraska, Sam Madden:
MIRIS: Fast Object Track Queries in Video. SIGMOD Conference 2020: 1907-1921 - [i49]Ryan Marcus, Parimarjan Negi, Hongzi Mao, Nesime Tatbul, Mohammad Alizadeh, Tim Kraska:
Bao: Learning to Steer Query Optimizers. CoRR abs/2004.03814 (2020) - [i48]Lujing Cen, Ryan Marcus, Hongzi Mao, Justin Gottschlich, Mohammad Alizadeh, Tim Kraska:
Learned Garbage Collection. CoRR abs/2004.13301 (2020) - [i41]Jialin Ding, Vikram Nathan, Mohammad Alizadeh, Tim Kraska:
Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads. CoRR abs/2006.13282 (2020) - [i39]Vikram Nathan, Jialin Ding, Tim Kraska, Mohammad Alizadeh:
Cortex: Harnessing Correlations to Boost Query Performance. CoRR abs/2012.06683 (2020) - 2019
- [j39]Ryan Marcus, Parimarjan Negi, Hongzi Mao, Chi Zhang, Mohammad Alizadeh, Tim Kraska, Olga Papaemmanouil, Nesime Tatbul:
Neo: A Learned Query Optimizer. Proc. VLDB Endow. 12(11): 1705-1718 (2019) - [c60]Tim Kraska, Mohammad Alizadeh, Alex Beutel, Ed H. Chi, Ani Kristo, Guillaume Leclerc, Samuel Madden, Hongzi Mao, Vikram Nathan:
SageDB: A Learned Database System. CIDR 2019 - [c55]Hongzi Mao, Parimarjan Negi, Akshay Narayan, Hanrui Wang, Jiacheng Yang, Haonan Wang, Ryan Marcus, Ravichandra Addanki, Mehrdad Khani Shirkoohi, Songtao He, Vikram Nathan, Frank Cangialosi, Shaileshh Bojja Venkatakrishnan, Wei-Hung Weng, Song Han, Tim Kraska, Mohammad Alizadeh:
Park: An Open Platform for Learning-Augmented Computer Systems. NeurIPS 2019: 2490-2502 - [i34]Ryan Marcus, Parimarjan Negi, Hongzi Mao, Chi Zhang, Mohammad Alizadeh, Tim Kraska, Olga Papaemmanouil, Nesime Tatbul:
Neo: A Learned Query Optimizer. CoRR abs/1904.03711 (2019) - [i29]Vikram Nathan, Jialin Ding, Mohammad Alizadeh, Tim Kraska:
Learning Multi-dimensional Indexes. CoRR abs/1912.01668 (2019)
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