Ryan Marcus
Ryan Marcus
MIT CSAIL
Verified email at csail.mit.edu - Homepage
Title
Cited by
Cited by
Year
Deep reinforcement learning for join order enumeration
R Marcus, O Papaemmanouil
aiDM'18 Proceedings of the First International Workshop on Exploiting …, 2018
1112018
Neo: A learned query optimizer
R Marcus, P Negi, H Mao, C Zhang, M Alizadeh, T Kraska, ...
PVLDB 12 (11), 1705-1718,, 2019
1102019
Towards a Hands-Free Query Optimizer through Deep Learning
R Marcus, O Papaemmanouil
CIDR 2019, 9th Biennial Conference on Innovative Data Systems Research, 2019
492019
Plan-structured deep neural network models for query performance prediction
R Marcus, O Papaemmanouil
PVLDB 12 (11), 1733–1746, 2019
472019
WiSeDB: a learning-based workload management advisor for cloud databases
R Marcus, O Papaemmanouil
PVLDB 9 (10), 780-791, 2016
412016
AI Meets AI: Leveraging Query Executions to Improve Index Recommendations
B Ding, S Das, R Marcus, W Wu, S Chaudhuri, VR Narasayya
2019 International Conference on Management of Data (SIGMOD ’19), 2019
352019
Park: An open platform for learning augmented computer systems
H Mao, P Negi, A Narayan, H Wang, J Yang, H Wang, R Marcus, ...
NeurIPS 2019 32, 2019
342019
RadixSpline: a single-pass learned index
A Kipf, R Marcus, A van Renen, M Stoian, A Kemper, T Kraska, ...
Proceedings of the Third International Workshop on Exploiting Artificial …, 2020
272020
Releasing Cloud Databases from the Chains of Performance Prediction Models
R Marcus, O Papaemmanouil
CIDR 2017, 8th Biennial Conference on Innovative Data Systems Research, 2017
212017
SOSD: A benchmark for learned indexes
A Kipf, R Marcus, A van Renen, M Stoian, A Kemper, T Kraska, ...
arXiv preprint arXiv:1911.13014, 2019
182019
NashDB: An End-to-End Economic Method for Elastic Database Fragmentation, Replication, and Provisioning
R Marcus, O Papaemmanouil, S Semenova, S Garber
2018 International Conference on Management of Data (SIGMOD ’18), 2018
16*2018
Benchmarking learned indexes
R Marcus, A Kipf, A van Renen, M Stoian, S Misra, A Kemper, T Neumann, ...
PVLDB 14 (1), 1-13, 2021
142021
ARDA: automatic relational data augmentation for machine learning
N Chepurko, R Marcus, E Zgraggen, RC Fernandez, T Kraska, D Karger
arXiv preprint arXiv:2003.09758, 2020
142020
Cdfshop: Exploring and optimizing learned index structures
R Marcus, E Zhang, T Kraska
Proceedings of the 2020 ACM SIGMOD International Conference on Management of …, 2020
102020
Bao: Learning to steer query optimizers
R Marcus, P Negi, H Mao, N Tatbul, M Alizadeh, T Kraska
arXiv preprint arXiv:2004.03814, 2020
102020
A learning-based service for cost and performance management of cloud databases (demo)
R Marcus, S Semenova, O Papaemmanouil
2017 IEEE 33rd International Conference on Data Engineering (ICDE), 1361-1362, 2017
102017
Cost-guided cardinality estimation: Focus where it matters
P Negi, R Marcus, H Mao, N Tatbul, T Kraska, M Alizadeh
2020 IEEE 36th International Conference on Data Engineering Workshops (ICDEW …, 2020
92020
MCMini: Monte Carlo on GPGPU
RC Marcus
Los Alamos National Lab.(LANL), Los Alamos, NM (United States), 2012
82012
Workload management for cloud databases via machine learning
R Marcus, O Papaemmanouil
2016 IEEE 32nd International Conference on Data Engineering Workshops (ICDEW …, 2016
52016
Buffer Pool Aware Query Scheduling via Deep Reinforcement Learning
C Zhang, R Marcus, A Kleiman, O Papaemmanouil
arXiv preprint arXiv:2007.10568, 2020
32020
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Articles 1–20