| Bridging the gap between ML solutions and their business requirements using feature interactions G Barash, E Farchi, I Jayaraman, O Raz, R Tzoref-Brill, M Zalmanovici Proceedings of the 2019 27th ACM Joint Meeting on European Software …, 2019 | 26 | 2019 |
| The association for the advancement of artificial intelligence 2020 workshop program G Bang, G Barash, R Bea, J Cali, M Castillo-Effen, X Chen, N Chhaya, ... Ai Magazine 41 (4), 100-114, 2020 | 6 | 2020 |
| Defending via strategic ML selection E Farchi, O Shehory, G Barash arXiv preprint arXiv:1904.00737, 2019 | 5 | 2019 |
| Theory and practice of quality assurance for machine learning systems S Ackerman, G Barash, E Farchi, O Raz, O Shehory New York: Springer, 2024 | 2* | 2024 |
| Learner-Independent Targeted Data Omission Attacks G Barash, O Shehory, S Kraus, E Farchi International Workshop on Engineering Dependable and Secure Machine Learning …, 2020 | 2 | 2020 |
| Optimal Integration of the ML Solution in the Business Decision Process S Ackerman, G Barash, E Farchi, O Raz, O Shehory Theory and Practice of Quality Assurance for Machine Learning Systems: An …, 2024 | | 2024 |
| Sequential Drift Detection S Ackerman, G Barash, E Farchi, O Raz, O Shehory Theory and Practice of Quality Assurance for Machine Learning Systems: An …, 2024 | | 2024 |
| Scientific Analysis of ML Systems S Ackerman, G Barash, E Farchi, O Raz, O Shehory Theory and Practice of Quality Assurance for Machine Learning Systems: An …, 2024 | | 2024 |
| Testing Solutions Based on Large Language Models S Ackerman, G Barash, E Farchi, O Raz, O Shehory Theory and Practice of Quality Assurance for Machine Learning Systems: An …, 2024 | | 2024 |
| Drift Detection by Measuring Distribution Differences S Ackerman, G Barash, E Farchi, O Raz, O Shehory Theory and Practice of Quality Assurance for Machine Learning Systems: An …, 2024 | | 2024 |
| A Detailed Chatbot Example S Ackerman, G Barash, E Farchi, O Raz, O Shehory Theory and Practice of Quality Assurance for Machine Learning Systems: An …, 2024 | | 2024 |
| A Framework Analysis for Alternating Components and Drift S Ackerman, G Barash, E Farchi, O Raz, O Shehory Theory and Practice of Quality Assurance for Machine Learning Systems: An …, 2024 | | 2024 |
| Unit Test vs. System Test of ML-Based Systems S Ackerman, G Barash, E Farchi, O Raz, O Shehory Theory and Practice of Quality Assurance for Machine Learning Systems: An …, 2024 | | 2024 |
| ML Testing S Ackerman, G Barash, E Farchi, O Raz, O Shehory Theory and Practice of Quality Assurance for Machine Learning Systems: An …, 2024 | | 2024 |
| Principles of Drift Detection and ML Solution Retraining S Ackerman, G Barash, E Farchi, O Raz, O Shehory Theory and Practice of Quality Assurance for Machine Learning Systems: An …, 2024 | | 2024 |
| Motivation and Best Practices for Machine Learning Designers and Testers S Ackerman, G Barash, E Farchi, O Raz, O Shehory Theory and Practice of Quality Assurance for Machine Learning Systems: An …, 2024 | | 2024 |
| Drift in Characterizations of Data S Ackerman, G Barash, E Farchi, O Raz, O Shehory Theory and Practice of Quality Assurance for Machine Learning Systems: An …, 2024 | | 2024 |
| Software testing in the machine learning era: Special issue of the empirical Software Engineering (EMSE) journal A Stocco, O Shehory, G Jahangirova, V Riccio, G Barash, E Farchi, ... Empirical Software Engineering 28 (3), 74, 2023 | | 2023 |
| Theory and Practice of Quality Assurance for Machine Learning Systems S Ackerman, G Barash, E Farchi, O Raz, O Shehory arXiv preprint arXiv:2201.00355, 2022 | | 2022 |
| Broadly Applicable Targeted Data Sample Omission Attacks G Barash, E Farchi, S Kraus, O Shehory arXiv preprint arXiv:2105.01560, 2021 | | 2021 |
Eitan FarchiIBM Research Lab in HaifaEmail confirmado em il.ibm.com