Raul Castro Fernandez

Orcid: 0000-0001-7675-6080

According to our database1, Raul Castro Fernandez authored at least 57 papers between 2013 and 2023.

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Bibliography

2023
Solo: Data Discovery Using Natural Language Questions Via A Self-Supervised Approach.
Proc. ACM Manag. Data, December, 2023

Cackle: Analytical Workload Cost and Performance Stability With Elastic Pools.
Proc. ACM Manag. Data, December, 2023

Data and AI Model Markets: Opportunities for Data and Model Sharing, Discovery, and Integration.
Proc. VLDB Endow., 2023

Saibot: A Differentially Private Data Search Platform.
Proc. VLDB Endow., 2023

How Large Language Models Will Disrupt Data Management.
Proc. VLDB Endow., 2023

Data-Sharing Markets: Model, Protocol, and Algorithms to Incentivize the Formation of Data-Sharing Consortia.
Proc. ACM Manag. Data, 2023

A Data-Centric Online Market for Machine Learning: From Discovery to Pricing.
CoRR, 2023

Making Differential Privacy Easier to Use for Data Controllers and Data Analysts using a Privacy Risk Indicator and an Escrow-Based Platform.
CoRR, 2023

Kitana: Efficient Data Augmentation Search for AutoML.
CoRR, 2023

Data Discovery using Natural Language Questions via a Self-Supervised Approach.
CoRR, 2023

Addressing Budget Allocation and Revenue Allocation in Data Market Environments Using an Adaptive Sampling Algorithm.
Proceedings of the International Conference on Machine Learning, 2023

Ver: View Discovery in the Wild.
Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

Metam: Goal-Oriented Data Discovery.
Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

2022
Revisiting Online Data Markets in 2022: A Seller and Buyer Perspective.
SIGMOD Rec., 2022

Data Station: Delegated, Trustworthy, and Auditable Computation to Enable Data-Sharing Consortia with a Data Escrow.
Proc. VLDB Endow., 2022

Enabling AI Innovation via Data and Model Sharing: An Overview of the Nsf Convergence Accelerator Track D.
AI Mag., 2022

Leva: Boosting Machine Learning Performance with Relational Embedding Data Augmentation.
Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

Protecting Data Markets from Strategic Buyers.
Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

2021
Niffler: A Reference Architecture and System Implementation for View Discovery over Pathless Table Collections by Example.
CoRR, 2021

Comprehensive and Comprehensible Data Catalogs: The What, Who, Where, When, Why, and How of Metadata Management.
CoRR, 2021

2020
Data Market Platforms: Trading Data Assets to Solve Data Problems.
Proc. VLDB Endow., 2020

ARDA: Automatic Relational Data Augmentation for Machine Learning.
Proc. VLDB Endow., 2020

The Data Station: Combining Data, Compute, and Market Forces.
CoRR, 2020

Data Market Platforms: Trading Data Assets to Solve Data Problems [Vision Paper].
CoRR, 2020

Starling: A Scalable Query Engine on Cloud Functions.
Proceedings of the 2020 International Conference on Management of Data, 2020

A System for Studying Deep Network Training.
Proceedings of the 10th Conference on Innovative Data Systems Research, 2020

2019
Dataset-On-Demand: Automatic View Search and Presentation for Data Discovery.
CoRR, 2019

Starling: A Scalable Query Engine on Cloud Function Services.
CoRR, 2019

Raha: A Configuration-Free Error Detection System.
Proceedings of the 2019 International Conference on Management of Data, 2019

Termite: a system for tunneling through heterogeneous data.
Proceedings of the Second International Workshop on Exploiting Artificial Intelligence Techniques for Data Management, 2019

Lazo: A Cardinality-Based Method for Coupled Estimation of Jaccard Similarity and Containment.
Proceedings of the 35th IEEE International Conference on Data Engineering, 2019

Data civilizer: end-to-end support for data discovery, integration, and cleaning.
Proceedings of the Making Databases Work: the Pragmatic Wisdom of Michael Stonebraker, 2019

Aurum: a story about research taste.
Proceedings of the Making Databases Work: the Pragmatic Wisdom of Michael Stonebraker, 2019

2018
Smallify: Learning Network Size while Training.
CoRR, 2018

Meta-Dataflows: Efficient Exploratory Dataflow Jobs.
Proceedings of the 2018 International Conference on Management of Data, 2018

FAHES: A Robust Disguised Missing Values Detector.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Building Data Civilizer Pipelines with an Advanced Workflow Engine.
Proceedings of the 34th IEEE International Conference on Data Engineering, 2018

Extracting Syntactical Patterns from Databases.
Proceedings of the 34th IEEE International Conference on Data Engineering, 2018

Seeping Semantics: Linking Datasets Using Word Embeddings for Data Discovery.
Proceedings of the 34th IEEE International Conference on Data Engineering, 2018

Aurum: A Data Discovery System.
Proceedings of the 34th IEEE International Conference on Data Engineering, 2018

2017
Extracting Syntactic Patterns from Databases.
CoRR, 2017

What to do about database decay.
Commun. ACM, 2017

A Demo of the Data Civilizer System.
Proceedings of the 2017 ACM International Conference on Management of Data, 2017

The Data Civilizer System.
Proceedings of the 8th Biennial Conference on Innovative Data Systems Research, 2017

2016
Stateful data-parallel processing.
PhD thesis, 2016

Quill: Efficient, Transferable, and Rich Analytics at Scale.
Proc. VLDB Endow., 2016

Detecting Data Errors: Where are we and what needs to be done?
Proc. VLDB Endow., 2016

SABER: Window-Based Hybrid Stream Processing for Heterogeneous Architectures.
Proceedings of the 2016 International Conference on Management of Data, 2016

Towards large-scale data discovery: position paper.
Proceedings of the Third International Workshop on Exploratory Search in Databases and the Web, 2016

Java2SDG: Stateful big data processing for the masses.
Proceedings of the 32nd IEEE International Conference on Data Engineering, 2016

The SABER system for window-based hybrid stream processing with GPGPUs: demo.
Proceedings of the 10th ACM International Conference on Distributed and Event-based Systems, 2016

Ako: Decentralised Deep Learning with Partial Gradient Exchange.
Proceedings of the Seventh ACM Symposium on Cloud Computing, 2016

2015
Liquid: Unifying Nearline and Offline Big Data Integration.
Proceedings of the Seventh Biennial Conference on Innovative Data Systems Research, 2015

2014
Making State Explicit for Imperative Big Data Processing.
Proceedings of the 2014 USENIX Annual Technical Conference, 2014

Scalable stateful stream processing for smart grids.
Proceedings of the 8th ACM International Conference on Distributed Event-Based Systems, 2014

2013
Integrating scale out and fault tolerance in stream processing using operator state management.
Proceedings of the ACM SIGMOD International Conference on Management of Data, 2013

Scalable and Fault-tolerant Stateful Stream Processing.
Proceedings of the 2013 Imperial College Computing Student Workshop, 2013


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