Arun Kumar

Thomas J. Parashos

Proc. VLDB Endow., February, 2024

2023

Saturn: An Optimized Data System for Multi-Large-Model Deep Learning Workloads.

[BibT_eX]

[DOI]

Proc. VLDB Endow., December, 2023

Lotan: Bridging the Gap between GNNs and Scalable Graph Analytics Engines.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2023

Saturn: Efficient Multi-Large-Model Deep Learning.

[BibT_eX]

[DOI]

CoRR, 2023

Saturn: An Optimized Data System for Large Model Deep Learning Workloads.

[BibT_eX]

[DOI]

CoRR, 2023

Database-Aware ASR Error Correction for Speech-to-SQL Parsing.

[BibT_eX]

[DOI]

Yutong Shao

Ndapa Nakashole

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

VLDB Scalable Data Science Category: The Inaugural Year.

[BibT_eX]

[DOI]

Alon Y. Halevy

Nesime Tatbul

SIGMOD Rec., 2022

Database Education at UC San Diego.

[BibT_eX]

[DOI]

Alin Deutsch

Amarnath Gupta

Babak Salimi

Victor Vianu

SIGMOD Rec., 2022

Structured Data Representation in Natural Language Interfaces.

[BibT_eX]

[DOI]

Yutong Shao

Ndapa Nakashole

IEEE Data Eng. Bull., 2022

Nautilus: An Optimized System for Deep Transfer Learning over Evolving Training Datasets.

[BibT_eX]

[DOI]

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

2021

VLDB Panel Summary: "The Future of Data(base) Education: Is the Cow Book Dead?".

[BibT_eX]

[DOI]

SIGMOD Rec., 2021

Distributed Deep Learning on Data Systems: A Comparative Analysis of Approaches.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2021

Errata for "Cerebro: A Data System for Optimized Deep Learning Model Selection".

[BibT_eX]

[DOI]

Supun Chathuranga Nakandala

Proc. VLDB Endow., 2021

Intermittent Human-in-the-Loop Model Selection using Cerebro: A Demonstration.

[BibT_eX]

[DOI]

Liangde Li

Proc. VLDB Endow., 2021

Towards an Optimized GROUP BY Abstraction for Large-Scale Machine Learning.

[BibT_eX]

[DOI]

Side Li

Proc. VLDB Endow., 2021

Front Matter.

[BibT_eX]

[DOI]

Alon Y. Halevy

Nesime Tatbul

Proc. VLDB Endow., 2021

Towards A Polyglot Framework for Factorized ML.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2021

Letter from the Rising Star Award Winner.

[BibT_eX]

[DOI]

IEEE Data Eng. Bull., 2021

Hydra: A System for Large Multi-Model Deep Learning.

[BibT_eX]

[DOI]

CoRR, 2021

Towards Benchmarking Feature Type Inference for AutoML Platforms.

[BibT_eX]

[DOI]

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

Automation of Data Prep, ML, and Data Science: New Cure or Snake Oil?

[BibT_eX]

[DOI]

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

Cerebro: A Layered Data Platform for Scalable Deep Learning.

[BibT_eX]

[DOI]

Proceedings of the 11th Conference on Innovative Data Systems Research, 2021

2020

Incremental and Approximate Computations for Accelerating Deep CNN Inference.

[BibT_eX]

[DOI]

ACM Trans. Database Syst., 2020

Query Optimization for Faster Deep CNN Explanations.

[BibT_eX]

[DOI]

SIGMOD Rec., 2020

Understanding and Benchmarking the Impact of GDPR on Database Systems.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2020

Cerebro: A Data System for Optimized Deep Learning Model Selection.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2020

SpeakQL: Towards Speech-driven Multimodal Querying of Structured Data.

[BibT_eX]

[DOI]

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

Vista: Optimized System for Declarative Feature Transfer from Deep CNNs at Scale.

[BibT_eX]

[DOI]

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

2019

Data Management in Machine Learning Systems

[BibT_eX]

[DOI]

Matthias Boehm

Jun Yang

Synthesis Lectures on Data Management, Morgan & Claypool Publishers, ISBN: 978-3-031-01869-5, 2019

Guest Editors' Introduction to the Special Section on the 33rd International Conference on Data Engineering (ICDE 2017).

[BibT_eX]

[DOI]

Wolfgang Gatterbauer

IEEE Trans. Knowl. Data Eng., 2019

Panorama: A Data System for Unbounded Vocabulary Querying over Video.

[BibT_eX]

[DOI]

Dimitris S. Papailiopoulos

Proc. VLDB Endow., 2019

Demonstration of Krypton: Optimized CNN Inference for Occlusion-based Deep CNN Explanations.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2019

Predicting Eating Events in Free Living Individuals - A Technical Report.

[BibT_eX]

[DOI]

CoRR, 2019

SysML: The New Frontier of Machine Learning Systems.

[BibT_eX]

[DOI]

Alexandros G. Dimakis

Anastasios Kyrillidis

Shivaram Venkataraman

CoRR, 2019

Demonstration of SpeakQL: Speech-driven Multimodal Querying of Structured Data.

[BibT_eX]

[DOI]

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

The ML Data Prep Zoo: Towards Semi-Automatic Data Preparation for ML.

[BibT_eX]

[DOI]

Proceedings of the 3rd International Workshop on Data Management for End-to-End Machine Learning, 2019

Cerebro: Efficient and Reproducible Model Selection on Deep Learning Systems.

[BibT_eX]

[DOI]

Proceedings of the 3rd International Workshop on Data Management for End-to-End Machine Learning, 2019

Incremental and Approximate Inference for Faster Occlusion-based Deep CNN Explanations.

[BibT_eX]

[DOI]

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

Tuple-oriented Compression for Large-scale Mini-batch Stochastic Gradient Descent.

[BibT_eX]

[DOI]

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

Enabling and Optimizing Non-linear Feature Interactions in Factorized Linear Algebra.

[BibT_eX]

[DOI]

Side Li

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

Demonstration of Nimbus: Model-based Pricing for Machine Learning in a Data Marketplace.

[BibT_eX]

[DOI]

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

Towards Model-based Pricing for Machine Learning in a Data Marketplace.

[BibT_eX]

[DOI]

Paraschos Koutris

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

Predicting Eating Events in Free Living Individuals.

[BibT_eX]

[DOI]

Proceedings of the 15th International Conference on eScience, 2019

2018

In-RDBMS Hardware Acceleration of Advanced Analytics.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2018

Model-based Pricing for Machine Learning in a Data Marketplace.

[BibT_eX]

[DOI]

Paraschos Koutris

CoRR, 2018

2017

Are Key-Foreign Key Joins Safe to Avoid when Learning High-Capacity Classifiers?

[BibT_eX]

[DOI]

Xiaojin Zhu

Proc. VLDB Endow., 2017

Towards Linear Algebra over Normalized Data.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2017

Stop That Join! Discarding Dimension Tables when Learning High Capacity Classifiers.

[BibT_eX]

[DOI]

Xiaojin Zhu

CoRR, 2017

When Lempel-Ziv-Welch Meets Machine Learning: A Case Study of Accelerating Machine Learning using Coding.

[BibT_eX]

[DOI]

CoRR, 2017

Data Management in Machine Learning: Challenges, Techniques, and Systems.

[BibT_eX]

[DOI]

Matthias Boehm

Jun Yang

Proceedings of the 2017 ACM International Conference on Management of Data, 2017

Model-based Pricing: Do Not Pay for More than What You Learn!

[BibT_eX]

[DOI]

Paraschos Koutris

Proceedings of the 1st Workshop on Data Management for End-to-End Machine Learning, 2017

SpeakQL: Towards Speech-driven Multi-modal Querying.

[BibT_eX]

[DOI]

Proceedings of the 2nd Workshop on Human-In-the-Loop Data Analytics, 2017

Bolt-on Differential Privacy for Scalable Stochastic Gradient Descent-based Analytics.

[BibT_eX]

[DOI]

Proceedings of the 2017 ACM International Conference on Management of Data, 2017

2016

Materialization Optimizations for Feature Selection Workloads.

[BibT_eX]

[DOI]

Ce Zhang

Christopher Ré

ACM Trans. Database Syst., 2016

Differentially Private Stochastic Gradient Descent for in-RDBMS Analytics.

[BibT_eX]

[DOI]

CoRR, 2016

To Join or Not to Join?: Thinking Twice about Joins before Feature Selection.

[BibT_eX]

[DOI]

Proceedings of the 2016 International Conference on Management of Data, 2016

2015

Model Selection Management Systems: The Next Frontier of Advanced Analytics.

[BibT_eX]

[DOI]

SIGMOD Rec., 2015

Demonstration of Santoku: Optimizing Machine Learning over Normalized Data.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2015

Learning Generalized Linear Models Over Normalized Data.

[BibT_eX]

[DOI]

Jeffrey F. Naughton

Jignesh M. Patel

Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, Melbourne, Victoria, Australia, May 31, 2015

2013

Feature Selection in Enterprise Analytics: A Demonstration using an R-based Data Analytics System.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2013

Hazy: making it easier to build and maintain big-data analytics.

[BibT_eX]

[DOI]

Feng Niu

Christopher Ré

Commun. ACM, 2013

Brainwash: A Data System for Feature Engineering.

[BibT_eX]

[DOI]

Proceedings of the Sixth Biennial Conference on Innovative Data Systems Research, 2013

2012

The MADlib Analytics Library or MAD Skills, the SQL.

[BibT_eX]

[DOI]

Joseph M. Hellerstein

Proc. VLDB Endow., 2012

Towards a unified architecture for in-RDBMS analytics.

[BibT_eX]

[DOI]

Proceedings of the ACM SIGMOD International Conference on Management of Data, 2012

2011

Probabilistic Management of OCR Data using an RDBMS.

[BibT_eX]

[DOI]