12 citations · 48 across the 17 of their papers we have counts for
3 papers · 2 filters
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…
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…