default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDRyan Marcus
Person information
- affiliation: University of Pennsylvania, Department of Computer and Information Science, Philadelphia, PA, USA
- affiliation: Massachusetts Institute of Technology (MIT), Computer Science and Artificial Intelligence Laboratory, Cambridge, MA, USA
- affiliation: Brandeis University, Waltham, MA, USA
Other persons with a similar name
SPARQL queries 
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
[j17]Chenyuan Wu, Mohammad Javad Amiri, Haoyun Qin, Bhavana Mehta, Ryan Marcus, Boon Thau Loo
:
Towards Full Stack Adaptivity in Permissioned Blockchains. Proc. VLDB Endow. 17(5): 1073-1080 (2024)- [j16]Haoyun Qin, Chenyuan Wu, Mohammad Javad Amiri, Ryan Marcus, Boon Thau Loo:
BFTGym: An Interactive Playground for BFT Protocols. Proc. VLDB Endow. 17(12): 4261-4264 (2024) - [j15]Chenyuan Wu, Haoyun Qin, Mohammad Javad Amiri, Boon Thau Loo, Dahlia Malkhi, Ryan Marcus:
Towards Truly Adaptive Byzantine Fault-Tolerant Consensus. ACM SIGOPS Oper. Syst. Rev. 58(1): 15-22 (2024) - [c26]Zixuan Yi, Yao Tian, Zachary G. Ives, Ryan Marcus:
Low Rank Approximation for Learned Query Optimization. aiDM@SIGMOD 2024: 4:1-4:5 - [c25]Ziniu Wu, Ryan Marcus, Zhengchun Liu, Parimarjan Negi, Vikram Nathan, Pascal Pfeil, Gaurav Saxena, Mohammad Rahman, Balakrishnan Narayanaswamy, Tim Kraska:
Stage: Query Execution Time Prediction in Amazon Redshift. SIGMOD Conference Companion 2024: 280-294 - [i28]Ziniu Wu, Ryan Marcus, Zhengchun Liu, Parimarjan Negi, Vikram Nathan, Pascal Pfeil, Gaurav Saxena, Mohammad Rahman, Balakrishnan Narayanaswamy, Tim Kraska:
Stage: Query Execution Time Prediction in Amazon Redshift. CoRR abs/2403.02286 (2024) - [i27]Chenyuan Wu, Haoyun Qin, Mohammad Javad Amiri, Boon Thau Loo, Dahlia Malkhi, Ryan Marcus:
BFTBrain: Adaptive BFT Consensus with Reinforcement Learning. CoRR abs/2408.06432 (2024) - [i26]Peizhi Wu, Haoshu Xu, Ryan Marcus, Zachary G. Ives:
A Practical Theory of Generalization in Selectivity Learning. CoRR abs/2409.07014 (2024) - [i25]Peter Akioyamen, Zixuan Yi, Ryan Marcus:
The Unreasonable Effectiveness of LLMs for Query Optimization. CoRR abs/2411.02862 (2024) - 2023
- [j14]Lyric Doshi, Vincent Zhuang, Gaurav Jain, Ryan Marcus, Haoyu Huang, Deniz Altinbüken, Eugene Brevdo, Campbell Fraser:
Kepler: Robust Learning for Parametric Query Optimization. Proc. ACM Manag. Data 1(1): 109:1-109:25 (2023) - [j13]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) - [j12]Chenyuan Wu, Bhavana Mehta, Mohammad Javad Amiri, Ryan Marcus, Boon Thau Loo:
AdaChain: A Learned Adaptive Blockchain. Proc. VLDB Endow. 16(8): 2033-2046 (2023) - [j11]Christoph Anneser, Nesime Tatbul, David E. Cohen, Zhenggang Xu, Prithviraj Pandian, Nikolay Laptev, Ryan Marcus:
AutoSteer: Learned Query Optimization for Any SQL Database. Proc. VLDB Endow. 16(12): 3515-3527 (2023) - [j10]Christoph Anneser, Mario Petruccelli, Nesime Tatbul, David E. Cohen, Zhenggang Xu, Prithviraj Pandian, Nikolay Laptev, Ryan Marcus, Alfons Kemper:
QO-Insight: Inspecting Steered Query Optimizers. Proc. VLDB Endow. 16(12): 3922-3925 (2023) - [c24]Gaurav Saxena, Mohammad Rahman, Naresh Chainani, Chunbin Lin, George Caragea, Fahim Chowdhury, Ryan Marcus, Tim Kraska, Ippokratis Pandis, Balakrishnan (Murali) Narayanaswamy:
Auto-WLM: Machine Learning Enhanced Workload Management in Amazon Redshift. SIGMOD Conference Companion 2023: 225-237 - [c23]Ryan Marcus:
Learned Query Superoptimization. VLDB Workshops 2023 - [c22]Bhavana Mehta, Neelesh C. A, Prashanth S. Iyer, Mohammad Javad Amiri, Boon Thau Loo, Ryan Marcus:
Towards Adaptive Fault-Tolerant Sharded Databases. VLDB Workshops 2023 - [i24]Ryan Marcus:
Learned Query Superoptimization. CoRR abs/2303.15308 (2023) - [i23]Lyric Doshi, Vincent Zhuang, Gaurav Jain, Ryan Marcus, Haoyu Huang, Deniz Altinbüken, Eugene Brevdo, Campbell Fraser:
Kepler: Robust Learning for Faster Parametric Query Optimization. CoRR abs/2306.06798 (2023) - [i22]Peizhi Wu, Ryan Marcus, Zachary G. Ives:
Adding Domain Knowledge to Query-Driven Learned Databases. CoRR abs/2312.01025 (2023) - 2022
- [j9]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) - [j8]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) - [c21]Andreas Kipf, Dominik Horn, Pascal Pfeil, Ryan Marcus, Tim Kraska:
LSI: a learned secondary index structure. aiDM@SIGMOD 2022: 4:1-4:5 - [c20]Rajesh Bordawekar, Yael Amsterdamer, Donatella Firmani, Ryan Marcus, Oded Shmueli:
aiDM'22: Fifth International Workshop on Exploiting Artificial Intelligence Techniques for Data Management. SIGMOD Conference 2022: 2550-2551 - [e1]Rajesh Bordawekar, Oded Shmueli, Yael Amsterdamer, Donatella Firmani, Ryan Marcus:
aiDM '22: Proceedings of the Fifth International Workshop on Exploiting Artificial Intelligence Techniques for Data Management, Philadelphia, Pennsylvania, USA, 17 June 2022. ACM 2022, ISBN 978-1-4503-9377-5 [contents] - [i21]Andreas Kipf, Dominik Horn, Pascal Pfeil, Ryan Marcus, Tim Kraska:
LSI: A Learned Secondary Index Structure. CoRR abs/2205.05769 (2022) - [i20]Chenyuan Wu, Bhavana Mehta, Mohammad Javad Amiri, Ryan Marcus, Boon Thau Loo:
AdaChain: A Learned Adaptive Blockchain. CoRR abs/2211.01580 (2022) - 2021
- [j7]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) - [c19]Laurent Bindschaedler, Andreas Kipf, Tim Kraska, Ryan Marcus, Umar Farooq Minhas:
Towards a Benchmark for Learned Systems. ICDE Workshops 2021: 127-133 - [c18]Lujing Cen, Andreas Kipf, Ryan Marcus, Tim Kraska:
LEA: A Learned Encoding Advisor for Column Stores. aiDM@SIGMOD 2021: 32-35 - [c17]Ryan Marcus, Parimarjan Negi, Hongzi Mao, Nesime Tatbul, Mohammad Alizadeh, Tim Kraska:
Bao: Making Learned Query Optimization Practical. SIGMOD Conference 2021: 1275-1288 - [c16]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 - [i19]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) - [i18]Lujing Cen, Andreas Kipf, Ryan Marcus, Tim Kraska:
LEA: A Learned Encoding Advisor for Column Stores. CoRR abs/2105.08830 (2021) - [i17]Mihail Stoian, Andreas Kipf, Ryan Marcus, Tim Kraska:
PLEX: Towards Practical Learned Indexing. CoRR abs/2108.05117 (2021) - 2020
- [j6]Nadiia Chepurko, Ryan Marcus, Emanuel Zgraggen, Raul Castro Fernandez, Tim Kraska, David R. Karger:
ARDA: Automatic Relational Data Augmentation for Machine Learning. Proc. VLDB Endow. 13(9): 1373-1387 (2020) - [j5]Ryan Marcus, Andreas Kipf, Alexander van Renen, Mihail Stoian, Sanchit Misra, Alfons Kemper, Thomas Neumann, Tim Kraska:
Benchmarking Learned Indexes. Proc. VLDB Endow. 14(1): 1-13 (2020) - [c15]Solomon Garber, Ryan Marcus, Antonella DiLillo, James A. Storer:
Low Rate Compression of Video with Dynamic Backgrounds. DCC 2020: 371 - [c14]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 - [c13]Lujing Cen, Ryan Marcus, Hongzi Mao, Justin Gottschlich, Mohammad Alizadeh, Tim Kraska:
Learned garbage collection. MAPL@PLDI 2020: 38-44 - [c12]Andreas Kipf, Ryan Marcus, Alexander van Renen, Mihail Stoian, Alfons Kemper, Tim Kraska, Thomas Neumann:
RadixSpline: a single-pass learned index. aiDM@SIGMOD 2020: 5:1-5:5 - [c11]Ryan Marcus, Emily Zhang, Tim Kraska:
CDFShop: Exploring and Optimizing Learned Index Structures. SIGMOD Conference 2020: 2789-2792 - [c10]Chi Zhang, Ryan Marcus, Anat Kleiman, Olga Papaemmanouil:
Buffer Pool Aware Query Scheduling via Deep Reinforcement Learning. AIDB@VLDB 2020 - [i16]Nadiia Chepurko, Ryan Marcus, Emanuel Zgraggen, Raul Castro Fernandez, Tim Kraska, David R. Karger:
ARDA: Automatic Relational Data Augmentation for Machine Learning. CoRR abs/2003.09758 (2020) - [i15]Fangke Ye, Shengtian Zhou, Anand Venkat, Ryan Marcus, Paul Petersen, Jesmin Jahan Tithi, Tim Mattson, Tim Kraska, Pradeep Dubey, Vivek Sarkar, Justin Gottschlich:
Context-Aware Parse Trees. CoRR abs/2003.11118 (2020) - [i14]Ryan Marcus, Parimarjan Negi, Hongzi Mao, Nesime Tatbul, Mohammad Alizadeh, Tim Kraska:
Bao: Learning to Steer Query Optimizers. CoRR abs/2004.03814 (2020) - [i13]Lujing Cen, Ryan Marcus, Hongzi Mao, Justin Gottschlich, Mohammad Alizadeh, Tim Kraska:
Learned Garbage Collection. CoRR abs/2004.13301 (2020) - [i12]Andreas Kipf, Ryan Marcus, Alexander van Renen, Mihail Stoian, Alfons Kemper, Tim Kraska, Thomas Neumann:
RadixSpline: A Single-Pass Learned Index. CoRR abs/2004.14541 (2020) - [i11]Fangke Ye, Shengtian Zhou, Anand Venkat, Ryan Marcus, Nesime Tatbul, Jesmin Jahan Tithi, Paul Petersen, Timothy G. Mattson, Tim Kraska, Pradeep Dubey, Vivek Sarkar, Justin Gottschlich:
MISIM: An End-to-End Neural Code Similarity System. CoRR abs/2006.05265 (2020) - [i10]Ryan Marcus, Andreas Kipf, Alexander van Renen, Mihail Stoian, Sanchit Misra, Alfons Kemper, Thomas Neumann, Tim Kraska:
Benchmarking Learned Indexes. CoRR abs/2006.12804 (2020) - [i9]Chi Zhang, Ryan Marcus, Anat Kleiman, Olga Papaemmanouil:
Buffer Pool Aware Query Scheduling via Deep Reinforcement Learning. CoRR abs/2007.10568 (2020) - [i8]Akhilesh Gupta, Nesime Tatbul, Ryan Marcus, Shengtian Zhou, Insup Lee, Justin Gottschlich:
Class-Weighted Evaluation Metrics for Imbalanced Data Classification. CoRR abs/2010.05995 (2020)
2010 – 2019
- 2019
- [j4]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) - [j3]Ryan Marcus, Olga Papaemmanouil:
Plan-Structured Deep Neural Network Models for Query Performance Prediction. Proc. VLDB Endow. 12(11): 1733-1746 (2019) - [j2]Ryan Marcus, Chi Zhang, Shuai Yu, Geoffrey Kao, Olga Papaemmanouil:
NashDB: Fragmentation, Replication, and Provisioning using Economic Methods. Proc. VLDB Endow. 12(12): 1830-1833 (2019) - [c9]Ryan Marcus, Olga Papaemmanouil:
Towards a Hands-Free Query Optimizer through Deep Learning. CIDR 2019 - [c8]Solomon Garber, Aaditya Prakash, Ryan Marcus, Antonella DiLillo, James A. Storer:
Compact Representations of Dynamic Video Background Using Motion Sprites. DCC 2019: 438-447 - [c7]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 - [c6]Bailu Ding, Sudipto Das, Ryan Marcus, Wentao Wu, Surajit Chaudhuri, Vivek R. Narasayya:
AI Meets AI: Leveraging Query Executions to Improve Index Recommendations. SIGMOD Conference 2019: 1241-1258 - [i7]Ryan Marcus, Olga Papaemmanouil:
Flexible Operator Embeddings via Deep Learning. CoRR abs/1901.09090 (2019) - [i6]Ryan Marcus, Olga Papaemmanouil:
Plan-Structured Deep Neural Network Models for Query Performance Prediction. CoRR abs/1902.00132 (2019) - [i5]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) - [i4]Andreas Kipf, Ryan Marcus, Alexander van Renen, Mihail Stoian, Alfons Kemper, Tim Kraska, Thomas Neumann:
SOSD: A Benchmark for Learned Indexes. CoRR abs/1911.13014 (2019) - 2018
- [c5]Ryan Marcus, Olga Papaemmanouil:
Deep Reinforcement Learning for Join Order Enumeration. aiDM@SIGMOD 2018: 3:1-3:4 - [c4]Ryan Marcus, Olga Papaemmanouil, Sofiya Semenova, Solomon Garber:
NashDB: An End-to-End Economic Method for Elastic Database Fragmentation, Replication, and Provisioning. SIGMOD Conference 2018: 1253-1267 - [i3]Ryan Marcus, Olga Papaemmanouil:
Deep Reinforcement Learning for Join Order Enumeration. CoRR abs/1803.00055 (2018) - [i2]Ryan Marcus, Olga Papaemmanouil:
Towards a Hands-Free Query Optimizer through Deep Learning. CoRR abs/1809.10212 (2018) - 2017
- [c3]Ryan Marcus, Olga Papaemmanouil:
Releasing Cloud Databases for the Chains of Performance Prediction Models. CIDR 2017 - [c2]Ryan Marcus, Sofiya Semenova, Olga Papaemmanouil:
A Learning-Based Service for Cost and Performance Management of Cloud Databases. ICDE 2017: 1361-1362 - 2016
- [j1]Ryan Marcus, Olga Papaemmanouil:
WiSeDB: A Learning-based Workload Management Advisor for Cloud Databases. Proc. VLDB Endow. 9(10): 780-791 (2016) - [c1]Ryan Marcus, Olga Papaemmanouil:
Workload management for cloud databases via machine learning. ICDE Workshops 2016: 27-30 - [i1]Ryan Marcus, Olga Papaemmanouil:
WiSeDB: A Learning-based Workload Management Advisor for Cloud Databases. CoRR abs/1601.08221 (2016)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2025-01-21 00:18 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
