Software systems that learn from data with AI and machine learning (ML) are becoming ubiquitous and are increasingly used to automate impactful decisions. The risks arising from this widespread use of AI/ML are garnering attention from policy makers, …
Software systems that learn from data with machine learning (ML) are used in critical decision-making processes. Unfortunately, real-world experience shows that the pipelines for data preparation, feature encoding and model training in ML systems are …
Software systems that learn from data are being deployed in increasing numbers in real-world application scenarios. It is a difficult and tedious task to ensure at development time that the end-to-end ML pipelines for such applications adhere to …
Software systems that learn from data with machine learning (ML) are used in critical decision-making processes. Unfortunately, real-world experience shows that the pipelines for data preparation, feature encoding and model training in ML systems are …
Software systems that learn from data with machine learning (ML) are ubiquitous. ML pipelines in these applications often suffer from a variety of data-related issues, such as data leakage, label errors or fairness violations, which require reasoning …
An important task of data scientists is to understand the sensitivity of their models to changes in the data that the models are trained and tested upon. Currently, conducting such data-centric what-if analyses requires significant and costly manual …
Software systems that learn from data are being deployed in increasing numbers in real world application scenarios. It is a difficult and tedious task to ensure at development time that the end-to-end ML pipelines for such applications adhere to …
Software systems that learn from user data with machine learning (ML) have become ubiquitous over the last years. Recent law such as the General Data Protection Regulation (GDPR) requires organisations that process personal data to delete user data …
Machine Learning (ML) is increasingly used to automate impactful decisions, and the risks arising from this wide-spread use are garnering attention from policymakers, scientists, and the media. ML applications are often very brittle with respect to …
Machine Learning (ML) is increasingly used to automate impactful decisions, and the risks arising from this wide-spread use are garnering attention from policy makers, scientists, and the media. ML applications are often very brittle with respect to …