31 citations · 78 across the 15 of their papers we have counts for
5 papers · 1 filter
Explainable Data Imputation using Constraints
Sandeep Hans, Diptikalyan Saha, Aniya Aggarwal
Data values in a dataset can be missing or anomalous due to mishandling or human error. Analysing data with missing values can create bias and affect the inferences. Several analys…
Automated Testing of AI Models
Swagatam Haldar, Deepak Vijaykeerthy, Diptikalyan Saha
The last decade has seen tremendous progress in AI technology and applications. With such widespread adoption, ensuring the reliability of the AI models is crucial. In past, we too…
Towards API Testing Across Cloud and Edge
Samuel Ackerman, Sanjib Choudhury, Nirmit Desai +5
API economy is driving the digital transformation of business applications across the hybrid Cloud and edge environments. For such transformations to succeed, end-to-end testing of…
AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias
Rachel K. E. Bellamy, Kuntal Dey, Michael Hind +15
Fairness is an increasingly important concern as machine learning models are used to support decision making in high-stakes applications such as mortgage lending, hiring, and priso…
Automated Test Generation to Detect Individual Discrimination in AI Models
Aniya Agarwal, Pranay Lohia, Seema Nagar +2
Dependability on AI models is of utmost importance to ensure full acceptance of the AI systems. One of the key aspects of the dependable AI system is to ensure that all its decisio…