E-LIB Suche - Ergebnisse für: Paleyes, Andrei

1

Can causality accelerate experimentation in software system..:

, In: Proceedings of the IEEE/ACM 3rd International Conference on AI Engineering - Software Engineering for AI,

Paleyes, Andrei ; Li, Han-Bo ; Lawrence, Neil D. - p. 280-281 , 2024

Link: https://dl.acm.org/doi/1..

2

Dataflow graphs as complete causal graphs:

, In: 2023 IEEE/ACM 2nd International Conference on AI Engineering – Software Engineering for AI (CAIN),

Paleyes, Andrei ; Guo, Siyuan ; Scholkopf, Bernhard. - p. 7-12 , 2023

Link: https://doi.org/10.1109/..

3

Causal fault localisation in dataflow systems:

, In: Proceedings of the 3rd Workshop on Machine Learning and Systems,

Paleyes, Andrei ; Lawrence, Neil David - p. 140-147 , 2023

Link: https://dl.acm.org/doi/1..

4

Challenges in Deploying Machine Learning: A Survey of Case ..:

Paleyes, Andrei ; Urma, Raoul-Gabriel ; Lawrence, Neil D.
ACM Computing Surveys. 55 (2022) 6 - p. 1-29 , 2022

Link: https://doi.org/10.1145/..

5

An empirical evaluation of flow based programming in the ma..:

, In: Proceedings of the 1st International Conference on AI Engineering: Software Engineering for AI,

Paleyes, Andrei ; Cabrera, Christian ; Lawrence, Neil D. - p. 54-64 , 2022

Link: https://dl.acm.org/doi/1..

6

An Empirical Evaluation of Flow Based Programming in the Ma..:

, In: 2022 IEEE/ACM 1st International Conference on AI Engineering – Software Engineering for AI (CAIN),

Paleyes, Andrei ; Cabrera, Christian ; Lawrence, Neil D. - p. 54-64 , 2022

Link: https://doi.org/10.1145/..

7

Good practices for Bayesian optimization of high dimensiona..:

Siivola, Eero ; Paleyes, Andrei ; González, Javier.
Applied AI Letters. 2 (2021) 2 - p. , 2021

Link: https://doi.org/10.1002/..

8

Automatic Discovery of Privacy–Utility Pareto Fronts:

Avent, Brendan ; González, Javier ; Diethe, Tom..
Proceedings on Privacy Enhancing Technologies. 2020 (2020) 4 - p. 5-23 , 2020

Link: https://doi.org/10.2478/..

9

Self-sustaining Software Systems (S4): Towards Improved Int..:

Cabrera, Christian ; Paleyes, Andrei ; Lawrence, Neil D
http://arxiv.org/abs/2401.11370. , 2024

Link: http://arxiv.org/abs/240..

10

Real-world Machine Learning Systems: A survey from a Data-O..:

Cabrera, Christian ; Paleyes, Andrei ; Thodoroff, Pierre.
http://arxiv.org/abs/2302.04810. , 2023

Link: http://arxiv.org/abs/230..

11

Automated discovery of trade-off between utility, privacy a..:

Ficiu, Bogdan ; Lawrence, Neil D ; Paleyes, Andrei
http://arxiv.org/abs/2311.15691. , 2023

Link: http://arxiv.org/abs/231..

12

Dataflow graphs as complete causal graphs:

Paleyes, Andrei ; Guo, Siyuan ; Schölkopf, Bernhard.
http://arxiv.org/abs/2303.09552. , 2023

Link: http://arxiv.org/abs/230..

13

Trieste: Efficiently Exploring The Depths of Black-box Func..:

Picheny, Victor ; Berkeley, Joel ; Moss, Henry B...
http://arxiv.org/abs/2302.08436. , 2023

Link: http://arxiv.org/abs/230..

14

Causal fault localisation in dataflow systems:

Paleyes, Andrei ; Lawrence, Neil D
http://arxiv.org/abs/2304.11987. , 2023

Link: http://arxiv.org/abs/230..

15

A penalisation method for batch multi-objective Bayesian op..:

Paleyes, Andrei ; Moss, Henry B ; Picheny, Victor..
http://arxiv.org/abs/2206.13326. , 2022

Link: http://arxiv.org/abs/220..