270 citations · 275 across the 4 of their papers we have counts for
6 papers
Locally Invariant Explanations: Towards Stable and Unidirectional Explanations through Local Invariant Learning
Amit Dhurandhar, Karthikeyan Ramamurthy, Kartik Ahuja +1
Locally interpretable model agnostic explanations (LIME) method is one of the most popular methods used to explain black-box models at a per example level. Although many variants h…
One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques
Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen +17
As artificial intelligence and machine learning algorithms make further inroads into society, calls are increasing from multiple stakeholders for these algorithms to explain their…
Blockchain Enabled Trustless API Marketplace
Vijay Arya, Sayandeep Sen, Palani Kodeswaran
There has been an unprecedented surge in the number of service providers offering a wide range of machine learning prediction APIs for tasks such as image classification, language…
Model Extraction Warning in MLaaS Paradigm
Manish Kesarwani, Bhaskar Mukhoty, Vijay Arya +1
Cloud vendors are increasingly offering machine learning services as part of their platform and services portfolios. These services enable the deployment of machine learning models…
Recovery of a Sparse Integer Solution to an Underdetermined System of Linear Equations
T. S. Jayram, Soumitra Pal, Vijay Arya
We consider a system of m linear equations in n variables Ax=b where A is a given m x n matrix and b is a given m-vector known to be equal to Ax' for some unknown solution x' that…
Sparsity without the Complexity: Loss Localisation using Tree Measurements
Vijay Arya, Darryl Veitch
We study network loss tomography based on observing average loss rates over a set of paths forming a tree -- a severely underdetermined linear problem for the unknown link loss pro…