Andrei Paleyes

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 22

Top Topics

Physical Processes

Software Systems

Automated Discovery

Top Venues

ACM Comput. Surv.

Publications

Andrei Paleyes, Han-Bo Li, Neil D. Lawrence
Can causality accelerate experimentation in software systems? CAIN (2024)
Christian Cabrera, Andrei Paleyes, Neil D. Lawrence
Self-sustaining Software Systems (S4): Towards Improved Interpretability and Adaptation. CoRR (2024)
Victor Picheny, Joel Berkeley, Henry B. Moss, Hrvoje Stojic, Uri Granta, Sebastian W. Ober, Artem Artemev, Khurram Ghani, Alexander Goodall, Andrei Paleyes, Sattar Vakili, Sergio Pascual-Diaz, Stratis Markou, Jixiang Qing, Nasrulloh R. B. S. Loka, Ivo Couckuyt
Trieste: Efficiently Exploring The Depths of Black-box Functions with TensorFlow. CoRR (2023)
Bogdan Ficiu, Neil D. Lawrence, Andrei Paleyes
Automated discovery of trade-off between utility, privacy and fairness in machine learning models. CoRR (2023)
Andrei Paleyes, Neil D. Lawrence
Causal fault localisation in dataflow systems. CoRR (2023)
Christian Cabrera, Andrei Paleyes, Pierre Thodoroff, Neil D. Lawrence
Real-world Machine Learning Systems: A survey from a Data-Oriented Architecture Perspective. CoRR (2023)
Andrei Paleyes, Siyuan Guo, Bernhard Schölkopf, Neil D. Lawrence
Dataflow graphs as complete causal graphs. CAIN (2023)
Andrei Paleyes, Siyuan Guo, Bernhard Schölkopf, Neil D. Lawrence
Dataflow graphs as complete causal graphs. CoRR (2023)
Andrei Paleyes, Neil David Lawrence
Causal fault localisation in dataflow systems. EuroMLSys@EuroSys (2023)
Andrei Paleyes, Raoul-Gabriel Urma, Neil D. Lawrence
Challenges in Deploying Machine Learning: A Survey of Case Studies. ACM Comput. Surv. 55 (6) (2023)
Sherif Akoush, Andrei Paleyes, Arnaud Van Looveren, Clive Cox
Desiderata for next generation of ML model serving. CoRR (2022)
Andrei Paleyes, Henry B. Moss, Victor Picheny, Piotr Zulawski, Felix Newman
A penalisation method for batch multi-objective Bayesian optimisation with application in heat exchanger design. CoRR (2022)
Andrei Paleyes, Christian Cabrera, Neil D. Lawrence
An Empirical Evaluation of Flow Based Programming in the Machine Learning Deployment Context. CoRR (2022)
Andrei Paleyes, Christian Cabrera, Neil D. Lawrence
An empirical evaluation of flow based programming in the machine learning deployment context. CAIN (2022)
Andrei Paleyes, Mark Pullin, Maren Mahsereci, Cliff McCollum, Neil D. Lawrence, Javier Gonzalez
Emulation of physical processes with Emukit. CoRR (2021)
Andrei Paleyes, Christian Cabrera, Neil D. Lawrence
Exploring the potential of flow-based programming for machine learning deployment in comparison with service-oriented architectures. CoRR (2021)
Eero Siivola, Javier Gonzalez, Andrei Paleyes, Aki Vehtari
Good practices for Bayesian Optimization of high dimensional structured spaces. CoRR (2020)
Virginia Aglietti, Xiaoyu Lu, Andrei Paleyes, Javier González
Causal Bayesian Optimization. CoRR (2020)
Andrei Paleyes, Raoul-Gabriel Urma, Neil D. Lawrence
Challenges in Deploying Machine Learning: a Survey of Case Studies. CoRR (2020)
Brendan Avent, Javier González, Tom Diethe, Andrei Paleyes, Borja Balle
Automatic Discovery of Privacy-Utility Pareto Fronts. Proc. Priv. Enhancing Technol. 2020 (4) (2020)
Virginia Aglietti, Xiaoyu Lu, Andrei Paleyes, Javier González
Causal Bayesian Optimization. AISTATS (2020)
Brendan Avent, Javier Gonzalez, Tom Diethe, Andrei Paleyes, Borja Balle
Automatic Discovery of Privacy-Utility Pareto Fronts. CoRR (2019)