166 citations · 261 across the 8 of their papers we have counts for
5 papers · 1 filter
Data Quality Toolkit: Automatic assessment of data quality and remediation for machine learning datasets
Nitin Gupta, Hima Patel, Shazia Afzal +10
The quality of training data has a huge impact on the efficiency, accuracy and complexity of machine learning tasks. Various tools and techniques are available that assess data qua…
Extracting Fairness Policies from Legal Documents
Rashmi Nagpal, Chetna Wadhwa, Mallika Gupta +3
Machine Learning community is recently exploring the implications of bias and fairness with respect to the AI applications. The definition of fairness for such applications varies…
Hardening Deep Neural Networks via Adversarial Model Cascades
Deepak Vijaykeerthy, Anshuman Suri, Sameep Mehta +1
Deep neural networks (DNNs) are vulnerable to malicious inputs crafted by an adversary to produce erroneous outputs. Works on securing neural networks against adversarial examples…
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…
Towards Crafting Text Adversarial Samples
Suranjana Samanta, Sameep Mehta
Adversarial samples are strategically modified samples, which are crafted with the purpose of fooling a classifier at hand. An attacker introduces specially crafted adversarial sam…