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09/12/2023
Enhancing In-Memory Spatial Indexing with Learned Search
Spatial data is ubiquitous. Massive amounts of data are generated every ...
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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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11/29/2021
Bounding the Last Mile: Efficient Learned String Indexing
We introduce the RadixStringSpline (RSS) learned index structure for eff...
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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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07/03/2021
When Are Learned Models Better Than Hash Functions?
In this work, we aim to study when learned models are better hash functi...
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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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10/23/2020
The Case for Distance-Bounded Spatial Approximations
Spatial approximations have been traditionally used in spatial databases...
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08/24/2020
The Case for Learned Spatial Indexes
Spatial data is ubiquitous. Massive amounts of data are generated every ...
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06/23/2020
Benchmarking Learned Indexes
Recent advancements in learned index structures propose replacing existi...
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05/06/2020
Fast Mapping onto Census Blocks
Pandemic measures such as social distancing and contact tracing can be e...
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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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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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08/21/2019
GeoBlocks: A Query-Driven Storage Layout for Geospatial Data
City authorities need to analyze urban geospatial data to improve transp...
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06/14/2019
DeepSPACE: Approximate Geospatial Query Processing with Deep Learning
The amount of the available geospatial data grows at an ever faster pace...
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04/17/2019
Estimating Cardinalities with Deep Sketches
We introduce Deep Sketches, which are compact models of databases that a...
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09/03/2018
Learned Cardinalities: Estimating Correlated Joins with Deep Learning
We describe a new deep learning approach to cardinality estimation. MSCN...
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02/26/2018