12 citations · 48 across the 17 of their papers we have counts for
5 papers · 1 filter
RankML: a Meta Learning-Based Approach for Pre-Ranking Machine Learning Pipelines
Doron Laadan, Roman Vainshtein, Yarden Curiel +2
The explosion of digital data has created multiple opportunities for organizations and individuals to leverage machine learning (ML) to transform the way they operate. However, the…
DeepLine: AutoML Tool for Pipelines Generation using Deep Reinforcement Learning and Hierarchical Actions Filtering
Yuval Heffetz, Roman Vainstein, Gilad Katz +1
Automatic machine learning (AutoML) is an area of research aimed at automating machine learning (ML) activities that currently require human experts. One of the most challenging ta…
Assessing the Quality of Scientific Papers
Roman Vainshtein, Gilad Katz, Bracha Shapira +1
A multitude of factors are responsible for the overall quality of scientific papers, including readability, linguistic quality, fluency,semantic complexity, and of course domain-sp…
New Item Consumption Prediction Using Deep Learning
Michael Shekasta, Gilad Katz, Asnat Greenstein-Messica +2
Recommendation systems have become ubiquitous in today's online world and are an integral part of practically every e-commerce platform. While traditional recommender systems use c…
Transferable Cost-Aware Security Policy Implementation for Malware Detection Using Deep Reinforcement Learning
Yoni Birman, Shaked Hindi, Gilad Katz +1
Malware detection is an ever-present challenge for all organizational gatekeepers, who must maintain high detection rates while minimizing interruptions to the organization's workf…