12 citations · 48 across the 17 of their papers we have counts for
3 papers · 1 filter
Hierarchical Deep Reinforcement Learning Approach for Multi-Objective Scheduling With Varying Queue Sizes
Yoni Birman, Ziv Ido, Gilad Katz +1
Multi-objective task scheduling (MOTS) is the task scheduling while optimizing multiple and possibly contradicting constraints. A challenging extension of this problem occurs when…
PIVEN: A Deep Neural Network for Prediction Intervals with Specific Value Prediction
Eli Simhayev, Gilad Katz, Lior Rokach
Improving the robustness of neural nets in regression tasks is key to their application in multiple domains. Deep learning-based approaches aim to achieve this goal either by impro…
Automatic Machine Learning Derived from Scholarly Big Data
Asnat Greenstein-Messica, Roman Vainshtein, Gilad Katz +2
One of the challenging aspects of applying machine learning is the need to identify the algorithms that will perform best for a given dataset. This process can be difficult, time c…