Interpretability and ADVERSITY

• Visualization in Data Science VDS@ KDD 2022     

Plant C, Hubig N, Shao J, Ottley A, Gou L, Möller T, Perer A, Lex A, Crisan A

Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining 

• Potentialfinder-Fostering Network Innovation by Connecting Data Owners Using Scaled Business-Relevant Pattern Recognition and Clustering 

A Abhinav, A Amle, R Bhandari, M Riechert, Nina Hubig

55th HICSS 2022 

• Exploiting explainable features to enhance DNN robustness   

Nina Hubig

under review

• Modeling Interaction Attribution Using Piece-wise Linear Approximation   

M Iqbal, Nina Hubig

under review

• How to defend your autonomous vehicle against perturbed traffic signs  

Nushrat Humaira, Nina Hubig

under review

• Quantifying Uncertainty in Model Agnostic Black-Box Explainability Methods 

Brandon Walker, Nina Hubig

KDD under review

• A Robust Adversarial Ensemble with Causal (Feature Interaction) Interpretations. 

Chunheng Zhao, Pierluigi Pisu, Nina Hubig

• Proactive Query Expansion for Streaming Data Using External Sources

Farah Alshanik, Nina Hubig, Amy Apon

• Explainable ̸= Secure: Membership Inference Attack Against Explainability