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06/11/2023
Kepler: Robust Learning for Faster Parametric Query Optimization
Most existing parametric query optimization (PQO) techniques rely on tra...
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03/27/2023
Learned Query Superoptimization
Traditional query optimizers are designed to be fast and stateless: each...
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11/03/2022
AdaChain: A Learned Adaptive Blockchain
This paper presents AdaChain, a learning-based blockchain framework that...
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05/11/2022
LSI: A Learned Secondary Index Structure
Learned index structures have been shown to achieve favorable lookup per...
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08/11/2021
Towards Practical Learned Indexing
Latest research proposes to replace existing index structures with learn...
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05/18/2021
LEA: A Learned Encoding Advisor for Column Stores
Data warehouses organize data in a columnar format to enable faster scan...
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01/13/2021
Flow-Loss: Learning Cardinality Estimates That Matter
Previous approaches to learned cardinality estimation have focused on im...
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10/12/2020
Class-Weighted Evaluation Metrics for Imbalanced Data Classification
Class distribution skews in imbalanced datasets may lead to models with ...
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07/21/2020
Buffer Pool Aware Query Scheduling via Deep Reinforcement Learning
In this extended abstract, we propose a new technique for query scheduli...
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06/23/2020
Benchmarking Learned Indexes
Recent advancements in learned index structures propose replacing existi...
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06/05/2020
MISIM: An End-to-End Neural Code Similarity System
Code similarity systems are integral to a range of applications from cod...
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04/30/2020
RadixSpline: A Single-Pass Learned Index
Recent research has shown that learned models can outperform state-of-th...
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04/28/2020
Learned Garbage Collection
Several programming languages use garbage collectors (GCs) to automatica...
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04/08/2020
Bao: Learning to Steer Query Optimizers
Query optimization remains one of the most challenging problems in data ...
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03/24/2020
Context-Aware Parse Trees
The simplified parse tree (SPT) presented in Aroma, a state-of-the-art c...
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03/21/2020
ARDA: Automatic Relational Data Augmentation for Machine Learning
Automatic machine learning () is a family of techniques to automate the ...
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11/29/2019
SOSD: A Benchmark for Learned Indexes
A groundswell of recent work has focused on improving data management sy...
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04/07/2019
Neo: A Learned Query Optimizer
Query optimization is one of the most challenging problems in database s...
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01/31/2019
Plan-Structured Deep Neural Network Models for Query Performance Prediction
Query performance prediction, the task of predicting the latency of a qu...
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01/25/2019
Flexible Operator Embeddings via Deep Learning
Integrating machine learning into the internals of database management s...
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09/26/2018
Towards a Hands-Free Query Optimizer through Deep Learning
Query optimization remains one of the most important and well-studied pr...
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02/28/2018
