Ryan Marcus

Orcid: 0000-0002-1279-1124

Affiliations:

University of Pennsylvania, Department of Computer and Information Science, Philadelphia, PA, USA
Massachusetts Institute of Technology (MIT), Computer Science and Artificial Intelligence Laboratory, Cambridge, MA, USA
Brandeis University, Waltham, MA, USA

According to our database¹, Ryan Marcus authored at least 53 papers between 2016 and 2024.

Collaborative distances:

Dijkstra number² of three.
Erdős number³ of three.

Timeline

Legend:

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In proceedings

Article

PhD thesis

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Bibliography

2024

BFTGym: An Interactive Playground for BFT Protocols.

[BibT_eX]

[DOI]

Proc. VLDB Endow., August, 2024

Towards Truly Adaptive Byzantine Fault-Tolerant Consensus.

[BibT_eX]

[DOI]

ACM SIGOPS Oper. Syst. Rev., June, 2024

Towards Full Stack Adaptivity in Permissioned Blockchains.

[BibT_eX]

[DOI]

Proc. VLDB Endow., January, 2024

A Practical Theory of Generalization in Selectivity Learning.

[BibT_eX]

[DOI]

CoRR, 2024

BFTBrain: Adaptive BFT Consensus with Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2024

Stage: Query Execution Time Prediction in Amazon Redshift.

[BibT_eX]

[DOI]

Balakrishnan Narayanaswamy

Tim Kraska

Proceedings of the Companion of the 2024 International Conference on Management of Data, 2024

Low Rank Approximation for Learned Query Optimization.

[BibT_eX]

[DOI]

Proceedings of the Seventh International Workshop on Exploiting Artificial Intelligence Techniques for Data Management, 2024

2023

AdaChain: A Learned Adaptive Blockchain.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2023

Robust Query Driven Cardinality Estimation under Changing Workloads.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2023

AutoSteer: Learned Query Optimization for Any SQL Database.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2023

QO-Insight: Inspecting Steered Query Optimizers.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2023

Kepler: Robust Learning for Parametric Query Optimization.

[BibT_eX]

[DOI]

Proc. ACM Manag. Data, 2023

Adding Domain Knowledge to Query-Driven Learned Databases.

[BibT_eX]

[DOI]

Peizhi Wu

Ryan Marcus

Zachary G. Ives

CoRR, 2023

Kepler: Robust Learning for Faster Parametric Query Optimization.

[BibT_eX]

[DOI]

CoRR, 2023

Towards Adaptive Fault-Tolerant Sharded Databases.

[BibT_eX]

[DOI]

Proceedings of the Joint Proceedings of Workshops at the 49th International Conference on Very Large Data Bases (VLDB 2023), Vancouver, Canada, August 28, 2023

Learned Query Superoptimization.

[BibT_eX]

[DOI]

Ryan Marcus

Proceedings of the Joint Proceedings of Workshops at the 49th International Conference on Very Large Data Bases (VLDB 2023), Vancouver, Canada, August 28, 2023

Auto-WLM: Machine Learning Enhanced Workload Management in Amazon Redshift.

[BibT_eX]

[DOI]

Balakrishnan (Murali) Narayanaswamy

Proceedings of the Companion of the 2023 International Conference on Management of Data, 2023

2022

Bao: Making Learned Query Optimization Practical.

[BibT_eX]

[DOI]

SIGMOD Rec., 2022

SageDB: An Instance-Optimized Data Analytics System.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2022

LSI: a learned secondary index structure.

[BibT_eX]

[DOI]

Proceedings of the aiDM '22: Proceedings of the Fifth International Workshop on Exploiting Artificial Intelligence Techniques for Data Management, 2022

aiDM'22: Fifth International Workshop on Exploiting Artificial Intelligence Techniques for Data Management.

[BibT_eX]

[DOI]

Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

2021

Flow-Loss: Learning Cardinality Estimates That Matter.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2021

PLEX: Towards Practical Learned Indexing.

[BibT_eX]

[DOI]

CoRR, 2021

Steering Query Optimizers: A Practical Take on Big Data Workloads.

[BibT_eX]

[DOI]

Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

LEA: A Learned Encoding Advisor for Column Stores.

[BibT_eX]

[DOI]

Proceedings of the aiDM '21: Fourth Workshop in Exploiting AI Techniques for Data Management, 2021

Towards a Benchmark for Learned Systems.

[BibT_eX]

[DOI]

Laurent Bindschaedler

Proceedings of the 37th IEEE International Conference on Data Engineering Workshops, 2021

2020

Benchmarking Learned Indexes.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2020

ARDA: Automatic Relational Data Augmentation for Machine Learning.

[BibT_eX]

[DOI]

Nadiia Chepurko

Ryan Marcus

Emanuel Zgraggen

Raul Castro Fernandez

Tim Kraska

David R. Karger

Proc. VLDB Endow., 2020

Class-Weighted Evaluation Metrics for Imbalanced Data Classification.

[BibT_eX]

[DOI]

CoRR, 2020

MISIM: An End-to-End Neural Code Similarity System.

[BibT_eX]

[DOI]

CoRR, 2020

Bao: Learning to Steer Query Optimizers.

[BibT_eX]

[DOI]

CoRR, 2020

Context-Aware Parse Trees.

[BibT_eX]

[DOI]

CoRR, 2020

Buffer Pool Aware Query Scheduling via Deep Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the AIDB@VLDB 2020, 2020

CDFShop: Exploring and Optimizing Learned Index Structures.

[BibT_eX]

[DOI]

Ryan Marcus

Emily Zhang

Tim Kraska

Proceedings of the 2020 International Conference on Management of Data, 2020

RadixSpline: a single-pass learned index.

[BibT_eX]

[DOI]

Proceedings of the Third International Workshop on Exploiting Artificial Intelligence Techniques for Data Management, 2020

Learned garbage collection.

[BibT_eX]

[DOI]

Proceedings of the 4th ACM SIGPLAN International Workshop on Machine Learning and Programming Languages, 2020

Cost-Guided Cardinality Estimation: Focus Where it Matters.

[BibT_eX]

[DOI]

Proceedings of the 36th IEEE International Conference on Data Engineering Workshops, 2020

Low Rate Compression of Video with Dynamic Backgrounds.

[BibT_eX]

[DOI]

Proceedings of the Data Compression Conference, 2020

2019

NashDB: Fragmentation, Replication, and Provisioning using Economic Methods.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2019

Plan-Structured Deep Neural Network Models for Query Performance Prediction.

[BibT_eX]

[DOI]

Ryan Marcus

Olga Papaemmanouil

Proc. VLDB Endow., 2019

Neo: A Learned Query Optimizer.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2019

SOSD: A Benchmark for Learned Indexes.

[BibT_eX]

[DOI]

CoRR, 2019

Flexible Operator Embeddings via Deep Learning.

[BibT_eX]

[DOI]

Ryan Marcus

Olga Papaemmanouil

CoRR, 2019

AI Meets AI: Leveraging Query Executions to Improve Index Recommendations.

[BibT_eX]

[DOI]

Proceedings of the 2019 International Conference on Management of Data, 2019

Park: An Open Platform for Learning-Augmented Computer Systems.

[BibT_eX]

[DOI]

Mehrdad Khani Shirkoohi

Songtao He

Vikram Nathan

Frank Cangialosi

Shaileshh Bojja Venkatakrishnan

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Compact Representations of Dynamic Video Background Using Motion Sprites.

[BibT_eX]

[DOI]

Proceedings of the Data Compression Conference, 2019

Towards a Hands-Free Query Optimizer through Deep Learning.

[BibT_eX]

[DOI]

Ryan Marcus

Olga Papaemmanouil

Proceedings of the 9th Biennial Conference on Innovative Data Systems Research, 2019

2018

NashDB: An End-to-End Economic Method for Elastic Database Fragmentation, Replication, and Provisioning.

[BibT_eX]

[DOI]

Proceedings of the 2018 International Conference on Management of Data, 2018

Deep Reinforcement Learning for Join Order Enumeration.

[BibT_eX]

[DOI]

Ryan Marcus

Olga Papaemmanouil

Proceedings of the First International Workshop on Exploiting Artificial Intelligence Techniques for Data Management, 2018

2017

A Learning-Based Service for Cost and Performance Management of Cloud Databases.

[BibT_eX]

[DOI]

Ryan Marcus

Sofiya Semenova

Olga Papaemmanouil

Proceedings of the 33rd IEEE International Conference on Data Engineering, 2017

Releasing Cloud Databases for the Chains of Performance Prediction Models.

[BibT_eX]

[DOI]

Ryan Marcus

Olga Papaemmanouil

Proceedings of the 8th Biennial Conference on Innovative Data Systems Research, 2017

2016

WiSeDB: A Learning-based Workload Management Advisor for Cloud Databases.

[BibT_eX]

[DOI]

Ryan Marcus

Olga Papaemmanouil

Proc. VLDB Endow., 2016

Workload management for cloud databases via machine learning.

[BibT_eX]

[DOI]

Ryan Marcus

Olga Papaemmanouil

Proceedings of the 32nd IEEE International Conference on Data Engineering Workshops, 2016

Ryan Marcus

Timeline

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