Articles with public access mandates - Muhammad Bilal ZafarLearn more
Not available anywhere: 1
Hands-on Tutorial:" Explanations in AI: Methods, Stakeholders and Pitfalls"
MC Mayer, MB Zafar, L Franceschi, H Rangwala
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023
Mandates: US National Science Foundation
Available somewhere: 8
A unified approach to quantifying algorithmic unfairness: Measuring individual &group unfairness via inequality indices
T Speicher, H Heidari, N Grgic-Hlaca, KP Gummadi, A Singla, A Weller, ...
Proceedings of the 24th ACM SIGKDD international conference on knowledge …, 2018
Mandates: UK Engineering and Physical Sciences Research Council
Quantifying Search Bias: Investigating Sources of Bias for Political Searches in Social Media
J Kulshrestha, M Eslami, J Messias, MB Zafar, S Ghosh, I Shibpur, ...
20th ACM Conference on Computer-Supported Cooperative Work and Social …, 2017
Mandates: US National Science Foundation
From Parity to Preference-based Notions of Fairness in Classification
MB Zafar, I Valera, MG Rodriguez, KP Gummadi, A Weller
31st Conference on Neural Information Processing Systems (NIPS), 2017
Mandates: UK Engineering and Physical Sciences Research Council
Beyond Distributive Fairness in Algorithmic Decision Making: Feature Selection for Procedurally Fair Learning
N Grgic-Hlaca, MB Zafar, KP Gummadi, A Weller
32nd AAAI Conference on Artificial Intelligence (AAAI-18), 2018
Mandates: UK Engineering and Physical Sciences Research Council
Inferring User Interests in the Twitter Social Network
P Bhattacharya, MB Zafar, N Ganguly, S Ghosh, KP Gummadi
8th ACM Conference on Recommender Systems (RecSys), 2014
Mandates: Department of Science & Technology, India
Loss-aversively fair classification
J Ali, MB Zafar, A Singla, KP Gummadi
Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 211-218, 2019
Mandates: European Commission
Counterfactual Accuracies for Alternative Models
U Bhatt, MB Zafar, K Gummadi, A Weller
ICLR Workshop on Machine Learning in Real Life Workshop 3, 2020
Mandates: UK Engineering and Physical Sciences Research Council
Reliable learning by subsuming a trusted model: Safe exploration of the space of complex models
T Speicher, MB Zafar, KP Gummadi, A Singla, A Weller
Proc. Int. Conf. Mach. Learn. Workshop (ICML), 1-5, 2017
Mandates: UK Engineering and Physical Sciences Research Council
Publication and funding information is determined automatically by a computer program