RECENT PAPERS
Classification with Fairness Constraints: A Meta-Algorithm with Provable Guarantees. [arXiv]
L. Elisa Celis, Lingxiao Huang, Vijay Keswani, Nisheeth K. Vishnoi
ACM FAT* 2019.
An Algorithmic Framework to Control Bias in Bandit-based Personalization. [arXiv]
L. Elisa Celis, Sayash Kapoor, Farnood Salehi, Nisheeth K. Vishnoi
ACM FAT* 2019.
Fair and Diverse Data Summarization. [arXiv]
L. Elisa Celis, Vijay Keswani, Damian Straszak, Amit Deshpande, Tarun
Kathuria, Nisheeth K. Vishnoi
ICML 2018.
Balanced News Using Constrained Bandit-based Personalization. [Demo Website] [Demo Video]
Sayash Kapoor, Vijay Keswani, Nisheeth K. Vishnoi, L. Elisa Celis
IJCAI-ECAI (Demo track) 2018.
Multiwinner voting with Fairness Constraints. [arxiv]
L. Elisa Celis, Lingxiao Huang, Nisheeth K. Vishnoi
IJCAI-ECAI 2018.
Ranking with Fairness Constraints. [arxiv]
L. Elisa Celis, Damian Straszak, Nisheeth K. Vishnoi
ICALP 2018.
Fair Personalization. [arxiv]
L. Elisa Celis, Nisheeth K. Vishnoi
Fairness, Accountability and Transparency in ML, 2017.
On the Complexity of Constrained Determinantal Point Processes. [arxiv]
L. Elisa Celis, Amit Deshpande, Tarun Kathuria, Damian Straszak, Nisheeth K. Vishnoi
RANDOM 2017.
How to be fair and diverse? [arxiv]
L. Elisa Celis, Amit Deshpande, Tarun Kathuria, Nisheeth K. Vishnoi
Fairness, Accountability and Transparency in ML, 2016 (Selected for presentation).
OTHER TOPICS
Alogrithms & Complexity, Optimization, Dynamical Systems, Probability
Natural Algorithms and Evolution