Richard Meyes
Orcid: 0000-0003-3797-0396
According to our database1,
Richard Meyes
authored at least 13 papers
between 2018 and 2024.
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Bibliography
2024
It's Not Always about Wide and Deep Models: Click-Through Rate Prediction with a Customer Behavior-Embedding Representation.
J. Theor. Appl. Electron. Commer. Res., March, 2024
Researchers' Concerns on Artificial Intelligence Ethics: Results from a Scenario-Based Survey.
Proceedings of the 7th ACM/IEEE International Workshop on Software-intensive Business, 2024
2022
On reliability of reinforcement learning based production scheduling systems: a comparative survey.
J. Intell. Manuf., 2022
Visual Interactive Exploration and Labeling of Large Volumes of Industrial Time Series Data.
Proceedings of the Enterprise Information Systems - 24th International Conference, 2022
Will This Online Shopping Session Succeed? Predicting Customer's Purchase Intention Using Embeddings.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022
2020
How Do You Act? An Empirical Study to Understand Behavior of Deep Reinforcement Learning Agents.
CoRR, 2020
Under the Hood of Neural Networks: Characterizing Learned Representations by Functional Neuron Populations and Network Ablations.
CoRR, 2020
2019
Multi-Agent Reinforcement Learning for Job Shop Scheduling in Flexible Manufacturing Systems.
Proceedings of the Second International Conference on Artificial Intelligence for Industries, 2019
2018