Search Results for author:
Found 4 papers, 0 papers with code
The Lokahi Prototype: Toward the automatic Extraction of Entity Relationship Models from Text
Entity relationship extraction envisions the automatic generation of semantic data models from collections of text, by automatic recognition of entities, by association of entities to form relationships, and by classifying these instances to assign them to entity sets (or classes) and relationship sets (or associations).
Efficient and Accurate In-Database Machine Learning with SQL Code Generation in Python
This motivates for further research in accuracy improvement and in IDBML with SQL code generation for big data and larger-than-memory datasets.
Addressing Algorithmic Bottlenecks in Elastic Machine Learning with Chicle
To address this, we propose Chicle, a new elastic distributed training framework which exploits the nature of machine learning algorithms to implement elasticity and load balancing without micro-tasks.
Elastic CoCoA: Scaling In to Improve Convergence
In this paper we experimentally analyze the convergence behavior of CoCoA and show, that the number of workers required to achieve the highest convergence rate at any point in time, changes over the course of the training.
