Andrei Paleyes

Orcid: 0000-0002-3703-8163

According to our database1, Andrei Paleyes authored at least 15 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2024
Self-sustaining Software Systems (S4): Towards Improved Interpretability and Adaptation.
CoRR, 2024

2023
Challenges in Deploying Machine Learning: A Survey of Case Studies.
ACM Comput. Surv., 2023

Automated discovery of trade-off between utility, privacy and fairness in machine learning models.
CoRR, 2023

Trieste: Efficiently Exploring The Depths of Black-box Functions with TensorFlow.
CoRR, 2023

Real-world Machine Learning Systems: A survey from a Data-Oriented Architecture Perspective.
CoRR, 2023

Causal fault localisation in dataflow systems.
Proceedings of the 3rd Workshop on Machine Learning and Systems, 2023

Dataflow graphs as complete causal graphs.
Proceedings of the 2nd IEEE/ACM International Conference on AI Engineering, 2023

2022
Desiderata for next generation of ML model serving.
CoRR, 2022

A penalisation method for batch multi-objective Bayesian optimisation with application in heat exchanger design.
CoRR, 2022

An empirical evaluation of flow based programming in the machine learning deployment context.
Proceedings of the 1st International Conference on AI Engineering: Software Engineering for AI, 2022

2021
Emulation of physical processes with Emukit.
CoRR, 2021

Exploring the potential of flow-based programming for machine learning deployment in comparison with service-oriented architectures.
CoRR, 2021

2020
Automatic Discovery of Privacy-Utility Pareto Fronts.
Proc. Priv. Enhancing Technol., 2020

Good practices for Bayesian Optimization of high dimensional structured spaces.
CoRR, 2020

Causal Bayesian Optimization.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020


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