Tim Kraska

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MIT

DBOS: A Proposal for a Data-Centric Operating System

Current operating systems are complex systems that were designed before ...
07/21/2020 ∙ by Michael Cafarella, et al. ∙ 0 ∙ share

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

Filtering data based on predicates is one of the most fundamental operat...
06/23/2020 ∙ by Jialin Ding, et al. ∙ 0 ∙ share

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Benchmarking Learned Indexes

Recent advancements in learned index structures propose replacing existi...
06/23/2020 ∙ by Ryan Marcus, et al. ∙ 0 ∙ share

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

Code similarity systems are integral to a range of applications from cod...
06/05/2020 ∙ by Fangke Ye, et al. ∙ 6 ∙ share

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Partitioned Learned Bloom Filter

Bloom filters are space-efficient probabilistic data structures that are...
06/05/2020 ∙ by Kapil Vaidya, et al. ∙ 0 ∙ share

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ExSample: Efficient Searches on Video Repositories through Adaptive Sampling

Capturing and processing video is increasingly common as cameras become ...
05/19/2020 ∙ by Oscar Moll, et al. ∙ 0 ∙ share

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Fast Mapping onto Census Blocks

Pandemic measures such as social distancing and contact tracing can be e...
05/06/2020 ∙ by Jeremy Kepner, et al. ∙ 0 ∙ share

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RadixSpline: A Single-Pass Learned Index

Recent research has shown that learned models can outperform state-of-th...
04/30/2020 ∙ by Andreas Kipf, et al. ∙ 0 ∙ share

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Learned Garbage Collection

Several programming languages use garbage collectors (GCs) to automatica...
04/28/2020 ∙ by Lujing Cen, et al. ∙ 0 ∙ share

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Bao: Learning to Steer Query Optimizers

Query optimization remains one of the most challenging problems in data ...
04/08/2020 ∙ by Ryan Marcus, et al. ∙ 0 ∙ share

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Context-Aware Parse Trees

The simplified parse tree (SPT) presented in Aroma, a state-of-the-art c...
03/24/2020 ∙ by Fangke Ye, et al. ∙ 7 ∙ share

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ARDA: Automatic Relational Data Augmentation for Machine Learning

Automatic machine learning () is a family of techniques to automate the ...
03/21/2020 ∙ by Nadiia Chepurko, et al. ∙ 17 ∙ share

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Learning Multi-dimensional Indexes

Scanning and filtering over multi-dimensional tables are key operations ...
12/03/2019 ∙ by Vikram Nathan, et al. ∙ 0 ∙ share

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SOSD: A Benchmark for Learned Indexes

A groundswell of recent work has focused on improving data management sy...
11/29/2019 ∙ by Andreas Kipf, et al. ∙ 0 ∙ share

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LISA: Towards Learned DNA Sequence Search

Next-generation sequencing (NGS) technologies have enabled affordable se...
10/10/2019 ∙ by Darryl Ho, et al. ∙ 0 ∙ share

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Sherlock: A Deep Learning Approach to Semantic Data Type Detection

Correctly detecting the semantic type of data columns is crucial for dat...
05/25/2019 ∙ by Madelon Hulsebos, et al. ∙ 0 ∙ share

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

Researchers currently rely on ad hoc datasets to train automated visuali...
05/12/2019 ∙ by Kevin Hu, et al. ∙ 0 ∙ share

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Neo: A Learned Query Optimizer

Query optimization is one of the most challenging problems in database s...
04/07/2019 ∙ by Ryan Marcus, et al. ∙ 0 ∙ share

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SysML: The New Frontier of Machine Learning Systems

Machine learning (ML) techniques are enjoying rapidly increasing adoptio...
03/29/2019 ∙ by Alexander Ratner, et al. ∙ 0 ∙ share

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How I Learned to Stop Worrying and Love Re-optimization

Cost-based query optimizers remain one of the most important components ...
02/21/2019 ∙ by Matthew Perron, et al. ∙ 0 ∙ share

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Custodes: Auditable Hypothesis Testing

We present Custodes: a new approach to solving the complex issue of prev...
01/19/2019 ∙ by Sacha Servan-Schreiber, et al. ∙ 0 ∙ share

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

Distributed transactions on high-overhead TCP/IP-based networks were con...
11/29/2018 ∙ by Erfan Zamanian, et al. ∙ 0 ∙ share

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VizRec: A framework for secure data exploration via visual representation

Visual representations of data (visualizations) are tools of great impor...
11/01/2018 ∙ by Lorenzo De Stefani, et al. ∙ 0 ∙ share

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Unknown Examples & Machine Learning Model Generalization

Over the past decades, researchers and ML practitioners have come up wit...
08/24/2018 ∙ by Yeounoh Chung, et al. ∙ 0 ∙ share

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VizML: A Machine Learning Approach to Visualization Recommendation

Data visualization should be accessible for all analysts with data, not ...
08/14/2018 ∙ by Kevin Z. Hu, et al. ∙ 8 ∙ share

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

As machine learning systems become democratized, it becomes increasingly...
07/16/2018 ∙ by Yeounoh Chung, et al. ∙ 0 ∙ share

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Slice Finder: Automated Data Slicing for Model Validation

As machine learning (ML) systems become democratized, it becomes increas...
07/16/2018 ∙ by Yeounoh Chung, et al. ∙ 0 ∙ share

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Slice Finder: Automated Data Sclicing for Model Validation

As machine learning (ML) systems become democratized, it becomes increas...
07/16/2018 ∙ by Yeounoh Chung, et al. ∙ 0 ∙ share

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Smallify: Learning Network Size while Training

As neural networks become widely deployed in different applications and ...
06/10/2018 ∙ by Guillaume Leclerc, et al. ∙ 0 ∙ share

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IDEBench: A Benchmark for Interactive Data Exploration

Existing benchmarks for analytical database systems such as TPC-DS and T...
04/07/2018 ∙ by Philipp Eichmann, et al. ∙ 0 ∙ share

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A-Tree: A Bounded Approximate Index Structure

Index structures are one of the most important tools that DBAs leverage ...
01/30/2018 ∙ by Alex Galakatos, et al. ∙ 0 ∙ share

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SuperNeurons: Dynamic GPU Memory Management for Training Deep Neural Networks

Going deeper and wider in neural architectures improves the accuracy, wh...
01/13/2018 ∙ by Linnan Wang, et al. ∙ 0 ∙ share

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The Case for Learned Index Structures

Indexes are models: a B-Tree-Index can be seen as a model to map a key t...
12/04/2017 ∙ by Tim Kraska, et al. ∙ 0 ∙ share

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Tim Kraska

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