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Expand your Training Limits! Generating Training Data for ML-based Data Management

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/s00778-014-0357-yopenalex-snapshot

The Stratosphere platform for big data analytics

inferredcites →https://doi.org/10.1007/s00778-019-00552-1openalex-snapshot

Snorkel: rapid training data creation with weak supervision.

inferredcites →https://doi.org/10.1007/s10115-012-0507-8openalex-snapshot

A survey on instance selection for active learning

inferredcites →https://doi.org/10.1007/s11263-014-0733-5openalex-snapshot

The Pascal Visual Object Classes Challenge: A Retrospective

inferredcites →https://doi.org/10.1007/s11263-015-0812-2openalex-snapshot

Do We Need More Training Data?

inferredcites →https://doi.org/10.1016/j.jmva.2015.06.009openalex-snapshot

On the asymptotics of random forests

inferredcites →https://doi.org/10.1023/a:1010933404324openalex-snapshot

Random Forests

inferredcites →https://doi.org/10.1109/icde.2012.64openalex-snapshot

Learning-based Query Performance Modeling and Prediction

inferredcites →https://doi.org/10.1109/icde48307.2020.00132openalex-snapshot

ML-based Cross-Platform Query Optimization

inferredcites →https://doi.org/10.1109/lsp.2017.2657381openalex-snapshot

Deep Convolutional Neural Networks and Data Augmentation for Environmental Sound Classification

inferredcites →https://doi.org/10.1145/1401890.1401950openalex-snapshot

Active learning with direct query construction

inferredcites →https://doi.org/10.1145/1807167.1807252openalex-snapshot

On active learning of record matching packages

inferredcites →https://doi.org/10.1145/2020408openalex-snapshot

Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining

inferredcites →https://doi.org/10.1145/2523813openalex-snapshot

A survey on concept drift adaptation

inferredcites →https://doi.org/10.1145/2934664openalex-snapshot

Apache Spark

inferredcites →https://doi.org/10.1145/312129.312285openalex-snapshot

The impact of changing populations on classifier performance

inferredcites →https://doi.org/10.1145/3196959.3196974openalex-snapshot

Active Learning of GAV Schema Mappings

inferredcites →https://doi.org/10.1145/3211954.3211957openalex-snapshot

Deep Reinforcement Learning for Join Order Enumeration

inferredcites →https://doi.org/10.1145/3219819.3219954openalex-snapshot

Scalable Active Learning by Approximated Error Reduction

inferredcites →https://doi.org/10.1145/3299869.3320218openalex-snapshot

Estimating Cardinalities with Deep Sketches

inferredcites →https://doi.org/10.1145/3299869.3324957openalex-snapshot

AI Meets AI

inferredcites →https://doi.org/10.1145/3318464.3389741openalex-snapshot

Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries

inferredcites →https://doi.org/10.1145/3318464.3389768openalex-snapshot

Active Learning for ML Enhanced Database Systems

inferredcites →https://doi.org/10.1145/3350489.3350494openalex-snapshot

Towards a real-time unsupervised estimation of predictive model degradation

inferredcites →https://doi.org/10.1145/3394486.3403063openalex-snapshot

NodeAug: Semi-Supervised Node Classification with Data Augmentation

inferredcites →https://doi.org/10.1145/3448016openalex-snapshot

Proceedings of the 2021 International Conference on Management of Data

inferredcites →https://doi.org/10.1145/3456859.3456861openalex-snapshot

Agora

inferredcites →https://doi.org/10.1145/369275.369291openalex-snapshot

New TPC benchmarks for decision support and web commerce

inferredcites →https://doi.org/10.1145/502512.502529openalex-snapshot

Mining time-changing data streams

inferredcites →https://doi.org/10.1145/564691.564766openalex-snapshot

Learning table access cardinalities with LEO

inferredcites →https://doi.org/10.1186/s40537-019-0197-0openalex-snapshot

A survey on Image Data Augmentation for Deep Learning

inferredcites →https://doi.org/10.14778/2556549.2556553openalex-snapshot

PREDIcT

inferredcites →https://doi.org/10.14778/2733085.2733092openalex-snapshot

Uncertainty aware query execution time prediction

inferredcites →https://doi.org/10.14778/2850583.2850594openalex-snapshot

How good are query optimizers, really?

inferredcites →https://doi.org/10.14778/3157794.3157797openalex-snapshot

Snorkel

inferredcites →https://doi.org/10.14778/3236187.3236195openalex-snapshot

RHEEM: enabling cross-platform data processing

inferredcites →https://doi.org/10.14778/3342263.3342644openalex-snapshot

Neo

inferredcites →https://doi.org/10.14778/3368289.3368294openalex-snapshot

Deep unsupervised cardinality estimation

inferredcites →https://doi.org/10.14778/3368289.3368296openalex-snapshot

An end-to-end learning-based cost estimator

inferredcites →https://doi.org/10.14778/3384345.3384349openalex-snapshot

DeepDB

inferredcites →https://doi.org/10.14778/3397230.3397238openalex-snapshot

Query performance prediction for concurrent queries using graph embedding

inferredcites →https://doi.org/10.4324/9780429443756openalex-snapshot

Applied Regression Analysis

inferredcites →https://doi.org/10.48550/arxiv.1808.03196openalex-snapshot

Learning to Optimize Join Queries With Deep Reinforcement Learning

inferredcites →https://doi.org/10.48550/arxiv.1901.09090openalex-snapshot

Flexible Operator Embeddings via Deep Learning

inferredcites →https://doi.org/10.5555/1248547.1248582openalex-snapshot

Quantile Regression Forests

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4963385openalex-extracted

inferred← citeshttps://doi.org/10.1002/sstr.202500720openalex-snapshot

Machine Learning Strategies to Circumvent Variabilities in Chemical Vapour‐Deposited Graphene Coatings for Remarkable Corrosion Resistance of Metals

inferred← citeshttps://doi.org/10.1007/s00778-023-00816-xopenalex-snapshot

Efficient and robust active learning methods for interactive database exploration

inferred← citeshttps://doi.org/10.1007/s00778-025-00947-3openalex-snapshot

FOSS: A learned doctor for query optimization

inferred← citeshttps://doi.org/10.1007/s10544-024-00707-0openalex-snapshot

Integrating optical and electrical sensing with machine learning for advanced particle characterization

inferred← citeshttps://doi.org/10.1109/icde53745.2022.00301openalex-snapshot

Database Optimizers in the Era of Learning

inferred← citeshttps://doi.org/10.1109/icde65448.2025.00369openalex-snapshot

Artemis: A Customizable Workload Generation Toolkit for Benchmarking Cardinality Estimation

inferred← citeshttps://doi.org/10.1109/tkde.2024.3484954openalex-snapshot

Hybrid Cost Modeling for Reducing Query Performance Regression in Index Tuning

inferred← citeshttps://doi.org/10.1109/tkde.2025.3563319openalex-snapshot

Data Synthesis Reinvented: Preserving Missing Patterns for Enhanced Analysis

inferred← citeshttps://doi.org/10.1109/tpds.2023.3298038openalex-snapshot

CLIC: An Extensible and Efficient Cross-Platform Data Analytics System

inferred← citeshttps://doi.org/10.1145/3543507.3583297openalex-snapshot

Preserving Missing Data Distribution in Synthetic Data

inferred← citeshttps://doi.org/10.1145/3626769openalex-snapshot

Rethinking Learned Cost Models: Why Start from Scratch?

inferred← citeshttps://doi.org/10.1145/3639276openalex-snapshot

Optimizing Dataflow Systems for Scalable Interactive Visualization

inferred← citeshttps://doi.org/10.1145/3641832.3641836openalex-snapshot

ML-Powered Index Tuning: An Overview of Recent Progress and Open Challenges

inferred← citeshttps://doi.org/10.1145/3725364openalex-snapshot

T3: Accurate and Fast Performance Prediction for Relational Database Systems With Compiled Decision Trees

inferred← citeshttps://doi.org/10.1145/3749185openalex-snapshot

TensorSocket: Shared Data Loading for Deep Learning Training

inferred← citeshttps://doi.org/10.14778/3551793.3551799openalex-snapshot

Zero-shot cost models for out-of-the-box learned cost prediction

inferred← citeshttps://doi.org/10.14778/3681954.3682030openalex-snapshot

Hit the Gym: Accelerating Query Execution to Efficiently Bootstrap Behavior Models for Self-Driving Database Management Systems

inferred← citeshttps://doi.org/10.14778/3750601.3750699openalex-snapshot

Learned Cost Models for Query Optimization: From Batch to Streaming Systems

inferred← citeshttps://doi.org/10.30574/ijsra.2024.11.1.1056openalex-snapshot

Data to AI: Building a solid data foundation for your generative AI applications in the cloud

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