Muhammad Bilal Zafar
Muhammad Bilal Zafar
Ruhr University Bochum & Research Center for Trustworthy Data Science and Security
Verified email at - Homepage
Cited by
Cited by
Fairness Constraints: Mechanisms for Fair Classification
MB Zafar, I Valera, MG Rodriguez, KP Gummadi
20th International Conference on Artificial Intelligence and Statistics …, 2017
Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment
MB Zafar, I Valera, MG Rodriguez, KP Gummadi
26th International World Wide Web Conference (WWW), 2017
Fairness constraints: A flexible approach for fair classification
MB Zafar, I Valera, M Gomez-Rodriguez, KP Gummadi
Journal of Machine Learning Research 20 (75), 1-42, 2019
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
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
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
The Case for Process Fairness in Learning: Feature Selection for Fair Decision Making
N Grgic-Hlaca, MB Zafar, KP Gummadi, A Weller
NIPS Symposium on ML and the Law, 2016
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
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
Search bias quantification: investigating political bias in social media and web search
J Kulshrestha, M Eslami, J Messias, MB Zafar, S Ghosh, KP Gummadi, ...
Information Retrieval Journal 22, 188-227, 2019
On Sampling the Wisdom of Crowds: Random vs. Expert Sampling of the Twitter Stream
S Ghosh, MB Zafar, P Bhattacharya, N Sharma, N Ganguly, K Gummadi
22nd ACM International Conference on Information & Knowledge Management …, 2013
Listening to Whispers of Ripple: Linking Wallets and Deanonymizing Transactions in the Ripple Network
P Moreno-Sanchez, MB Zafar, A Kate
Privacy Enhancing Technologies Symposium (PETS), 2016
Fair bayesian optimization
V Perrone, M Donini, MB Zafar, R Schmucker, K Kenthapadi, ...
Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, 854-863, 2021
Strength in Numbers: Robust Tamper Detection in Crowd Computations
B Viswanath, MA Bashir, MB Zafar, S Bouget, S Guha, KP Gummadi, ...
2015 ACM Conference on Online Social Networks (COSN), 2015
Deep Twitter Diving: Exploring Topical Groups in Microblogs at Scale
P Bhattacharya, S Ghosh, J Kulshrestha, M Mondal, MB Zafar, N Ganguly, ...
17th ACM Conference on Computer-Supported Cooperative Work & Social …, 2014
Sampling Content from Online Social Networks: Comparing Random vs. Expert Sampling of the Twitter Stream
MB Zafar, P Bhattacharya, N Ganguly, KP Gummadi, S Ghosh
ACM Transactions on the Web (TWEB), 2015
Characterizing Information Diets of Social Media Users
J Kulshrestha, MB Zafar, LE Noboa, KP Gummadi, S Ghosh
9th International AAAI Conference on Web and Social Media (ICWSM), 2015
Amazon sagemaker clarify: Machine learning bias detection and explainability in the cloud
M Hardt, X Chen, X Cheng, M Donini, J Gelman, S Gollaprolu, J He, ...
Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data …, 2021
On Fairness, Diversity and Randomness in Algorithmic Decision Making
N Grgić-Hlača, MB Zafar, KP Gummadi, A Weller
4th Workshop on Fairness, Accountability, and Transparency in Machine …, 2017
Amazon sagemaker model monitor: A system for real-time insights into deployed machine learning models
D Nigenda, Z Karnin, MB Zafar, R Ramesha, A Tan, M Donini, ...
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022
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