[PDF][PDF] A review paper on artificial intelligence at the service of human resources management
S Berhil, H Benlahmar, N Labani - Indonesian Journal of Electrical …, 2020 - academia.edu
In the last few years, all companies have been interested in the analysis of data related to
Human Resources and have focused on human capital, which is considered as the major …
Human Resources and have focused on human capital, which is considered as the major …
Exploring the role of machine learning in scientific workflows: Opportunities and challenges
In this survey, we discuss the challenges of executing scientific workflows as well as existing
Machine Learning (ML) techniques to alleviate those challenges. We provide the context …
Machine Learning (ML) techniques to alleviate those challenges. We provide the context …
Distributed Bayesian optimization of deep reinforcement learning algorithms
Significant strides have been made in supervised learning settings thanks to the successful
application of deep learning. Now, recent work has brought the techniques of deep learning …
application of deep learning. Now, recent work has brought the techniques of deep learning …
[PDF][PDF] A Study of Job Failure Prediction at Job Submit-State and Job Start-State in High-Performance Computing System: Using Decision Tree Algorithms [J]
A Banjongkan, W Pongsena, N Kerdprasop… - Journal of Advances in …, 2021 - academia.edu
In High-Performance Computing (HPC) system, job failure is a major problem because it
means the losses in computation time, resources, and power. Job failure also degrades …
means the losses in computation time, resources, and power. Job failure also degrades …
Hyperspace: Distributed bayesian hyperparameter optimization
MT Young, J Hinkle, A Ramanathan… - … Architecture and High …, 2018 - ieeexplore.ieee.org
As machine learning models continue to increase in complexity, so does the potential
number of free model parameters commonly known as hyperparameters. While there has …
number of free model parameters commonly known as hyperparameters. While there has …
Improving flood forecasting through feature selection by a genetic algorithm–experiments based on real data from an amazon rainforest river
This paper addresses the problem of feature selection aiming to improve a flood forecasting
model. The proposed model is carried out through a case study that uses 18 different time …
model. The proposed model is carried out through a case study that uses 18 different time …
Keeping track of user steering actions in dynamic workflows
In long-lasting scientific workflow executions in HPC machines, computational scientists (the
users in this work) often need to fine-tune several workflow parameters. These tunings are …
users in this work) often need to fine-tune several workflow parameters. These tunings are …
Provenance of dynamic adaptations in user-steered dataflows
Due to the exploratory nature of scientific experiments, computational scientists need to
steer dataflows running on High-Performance Computing (HPC) machines by tuning …
steer dataflows running on High-Performance Computing (HPC) machines by tuning …
A comprehensive modeling approach for crop yield forecasts using AI-based methods and crop simulation models
Numerous solutions for yield estimation are either based on data-driven models, or on crop-
simulation models (CSMs). Researchers tend to build data-driven models using nationwide …
simulation models (CSMs). Researchers tend to build data-driven models using nationwide …
Development of geo-spatial physical models using historical lineage data
One embodiment provides a method for recommending model characteristics to be used in
developing a target geo-spatial physical model for a target geographic location utilizing …
developing a target geo-spatial physical model for a target geographic location utilizing …