b'Tim Kraska'

research

∙ 05/08/2023

Parallel External Sorting of ASCII Records Using Learned Models

External sorting is at the core of many operations in large-scale databa...

0 Ani Kristo, et al. ∙

research

∙ 12/11/2022

FactorJoin: A New Cardinality Estimation Framework for Join Queries

Cardinality estimation is one of the most fundamental and challenging pr...

0 Ziniu Wu, et al. ∙

research

∙ 05/11/2022

LSI: A Learned Secondary Index Structure

Learned index structures have been shown to achieve favorable lookup per...

0 Andreas Kipf, et al. ∙

research

∙ 11/29/2021

Bounding the Last Mile: Efficient Learned String Indexing

We introduce the RadixStringSpline (RSS) learned index structure for eff...

0 Benjamin Spector, et al. ∙

research

∙ 11/16/2021

The Case for Learned In-Memory Joins

In-memory join is an essential operator in any database engine. It has b...

0 Ibrahim Sabek, et al. ∙

research

∙ 08/11/2021

Towards Practical Learned Indexing

Latest research proposes to replace existing index structures with learn...

0 Mihail Stoian, et al. ∙

research

∙ 07/05/2021

Defeating duplicates: A re-design of the LearnedSort algorithm

LearnedSort is a novel sorting algorithm that, unlike traditional method...

0 Ani Kristo, et al. ∙

research

∙ 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...

0 Ibrahim Sabek, et al. ∙

research

∙ 05/18/2021

LEA: A Learned Encoding Advisor for Column Stores

Data warehouses organize data in a columnar format to enable faster scan...

0 Lujing Cen, et al. ∙

research

∙ 03/26/2021

SkyQuery: An Aerial Drone Video Sensing Platform

Video-based sensing from aerial drones, especially small multirotor dron...

0 Favyen Bastani, et al. ∙

research

∙ 03/24/2021

TagMe: GPS-Assisted Automatic Object Annotation in Videos

Training high-accuracy object detection models requires large and divers...

0 Songtao He, et al. ∙

research

∙ 01/13/2021

Flow-Loss: Learning Cardinality Estimates That Matter

Previous approaches to learned cardinality estimation have focused on im...

0 Parimarjan Negi, et al. ∙

research

∙ 12/12/2020

Cortex: Harnessing Correlations to Boost Query Performance

Databases employ indexes to filter out irrelevant records, which reduces...

0 Vikram Nathan, et al. ∙

research

∙ 07/21/2020

DBOS: A Proposal for a Data-Centric Operating System

Current operating systems are complex systems that were designed before ...

0 Michael Cafarella, et al. ∙

research

∙ 06/23/2020

Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads

Filtering data based on predicates is one of the most fundamental operat...

0 Jialin Ding, et al. ∙

research

∙ 06/23/2020

Benchmarking Learned Indexes

Recent advancements in learned index structures propose replacing existi...

0 Ryan Marcus, et al. ∙

research

∙ 06/05/2020

MISIM: An End-to-End Neural Code Similarity System

Code similarity systems are integral to a range of applications from cod...

6 Fangke Ye, et al. ∙

research

∙ 06/05/2020

Partitioned Learned Bloom Filter

Bloom filters are space-efficient probabilistic data structures that are...

0 Kapil Vaidya, et al. ∙

research

∙ 05/19/2020

ExSample: Efficient Searches on Video Repositories through Adaptive Sampling

Capturing and processing video is increasingly common as cameras become ...

0 Oscar Moll, et al. ∙

research

∙ 05/06/2020

Fast Mapping onto Census Blocks

Pandemic measures such as social distancing and contact tracing can be e...

0 Jeremy Kepner, et al. ∙

research

∙ 04/30/2020

RadixSpline: A Single-Pass Learned Index

Recent research has shown that learned models can outperform state-of-th...

0 Andreas Kipf, et al. ∙

research

∙ 04/28/2020

Learned Garbage Collection

Several programming languages use garbage collectors (GCs) to automatica...

0 Lujing Cen, et al. ∙

research

∙ 04/08/2020

Bao: Learning to Steer Query Optimizers

Query optimization remains one of the most challenging problems in data ...

0 Ryan Marcus, et al. ∙

research

∙ 03/24/2020

Context-Aware Parse Trees

The simplified parse tree (SPT) presented in Aroma, a state-of-the-art c...

7 Fangke Ye, et al. ∙

research

∙ 03/21/2020

ARDA: Automatic Relational Data Augmentation for Machine Learning

Automatic machine learning () is a family of techniques to automate the ...

17 Nadiia Chepurko, et al. ∙

research

∙ 12/03/2019

Learning Multi-dimensional Indexes

Scanning and filtering over multi-dimensional tables are key operations ...

0 Vikram Nathan, et al. ∙

research

∙ 11/29/2019

SOSD: A Benchmark for Learned Indexes

A groundswell of recent work has focused on improving data management sy...

0 Andreas Kipf, et al. ∙

research

∙ 10/10/2019

LISA: Towards Learned DNA Sequence Search

Next-generation sequencing (NGS) technologies have enabled affordable se...

0 Darryl Ho, et al. ∙

research

∙ 05/25/2019

Sherlock: A Deep Learning Approach to Semantic Data Type Detection

Correctly detecting the semantic type of data columns is crucial for dat...

0 Madelon Hulsebos, et al. ∙

research

∙ 05/12/2019

VizNet: Towards A Large-Scale Visualization Learning and Benchmarking Repository

Researchers currently rely on ad hoc datasets to train automated visuali...

0 Kevin Hu, et al. ∙

research

∙ 04/07/2019

Neo: A Learned Query Optimizer

Query optimization is one of the most challenging problems in database s...

0 Ryan Marcus, et al. ∙

research

∙ 03/29/2019

SysML: The New Frontier of Machine Learning Systems

Machine learning (ML) techniques are enjoying rapidly increasing adoptio...

0 Alexander Ratner, et al. ∙

research

∙ 02/21/2019

How I Learned to Stop Worrying and Love Re-optimization

Cost-based query optimizers remain one of the most important components ...

0 Matthew Perron, et al. ∙

research

∙ 01/19/2019

Custodes: Auditable Hypothesis Testing

We present Custodes: a new approach to solving the complex issue of prev...

0 Sacha Servan-Schreiber, et al. ∙

research

∙ 11/29/2018

Chiller: Contention-centric Transaction Execution and Data Partitioning for Fast Networks

Distributed transactions on high-overhead TCP/IP-based networks were con...

0 Erfan Zamanian, et al. ∙

research

∙ 11/01/2018

VizRec: A framework for secure data exploration via visual representation

Visual representations of data (visualizations) are tools of great impor...

0 Lorenzo De Stefani, et al. ∙

research

∙ 08/24/2018

Unknown Examples & Machine Learning Model Generalization

Over the past decades, researchers and ML practitioners have come up wit...

0 Yeounoh Chung, et al. ∙

research

∙ 08/14/2018

VizML: A Machine Learning Approach to Visualization Recommendation

Data visualization should be accessible for all analysts with data, not ...

8 Kevin Z. Hu, et al. ∙

research

∙ 07/16/2018

Automated Data Slicing for Model Validation:A Big data - AI Integration Approach

As machine learning systems become democratized, it becomes increasingly...

0 Yeounoh Chung, et al. ∙

research

∙ 07/16/2018

Slice Finder: Automated Data Slicing for Model Validation

As machine learning (ML) systems become democratized, it becomes increas...

0 Yeounoh Chung, et al. ∙

research

∙ 07/16/2018

Slice Finder: Automated Data Sclicing for Model Validation

As machine learning (ML) systems become democratized, it becomes increas...

0 Yeounoh Chung, et al. ∙

research

∙ 06/10/2018

Smallify: Learning Network Size while Training

As neural networks become widely deployed in different applications and ...

0 Guillaume Leclerc, et al. ∙

research

∙ 04/07/2018

IDEBench: A Benchmark for Interactive Data Exploration

Existing benchmarks for analytical database systems such as TPC-DS and T...

0 Philipp Eichmann, et al. ∙

research

∙ 01/30/2018

A-Tree: A Bounded Approximate Index Structure

Index structures are one of the most important tools that DBAs leverage ...

0 Alex Galakatos, et al. ∙

research

∙ 01/13/2018

SuperNeurons: Dynamic GPU Memory Management for Training Deep Neural Networks

Going deeper and wider in neural architectures improves the accuracy, wh...

0 Linnan Wang, et al. ∙

research

∙ 12/04/2017

The Case for Learned Index Structures

Indexes are models: a B-Tree-Index can be seen as a model to map a key t...

0 Tim Kraska, et al. ∙

Tim Kraska

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