activity
20182023
most citedTowards Demystifying Serverless Machine Learning Training

106 citations · 152 across the 13 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

cs.DB2019

Lambada: Interactive Data Analytics on Cold Data using Serverless Cloud Infrastructure

Ingo Müller, Renato Marroquín, Gustavo Alonso

The promise of ultimate elasticity and operational simplicity of serverless computing has recently lead to an explosion of research in this area. In the context of data analytics,…

cs.DB2019

Rumble: Data Independence for Large Messy Data Sets

Ingo Müller, Ghislain Fourny, Stefan Irimescu +2

This paper introduces Rumble, a query execution engine for large, heterogeneous, and nested collections of JSON objects built on top of Apache Spark. While data sets of this type a…

cs.DB2019

Demystifying Graph Databases: Analysis and Taxonomy of Data Organization, System Designs, and Graph Queries

Maciej Besta, Robert Gerstenberger, Emanuel Peter +5

Graph processing has become an important part of multiple areas of computer science, such as machine learning, computational sciences, medical applications, social network analysis…

cs.LG2019

MLSys: The New Frontier of Machine Learning Systems

Alexander Ratner, Dan Alistarh, Gustavo Alonso +66

Machine learning (ML) techniques are enjoying rapidly increasing adoption. However, designing and implementing the systems that support ML models in real-world deployments remains…

cs.DS2019★ 23 cited

Accelerating Generalized Linear Models with MLWeaving: A One-Size-Fits-All System for Any-precision Learning (Technical Report)

Zeke Wang, Kaan Kara, Hantian Zhang +3

Learning from the data stored in a database is an important function increasingly available in relational engines. Methods using lower precision input data are of special interest…