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Preetam Nandy
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2020 – today
- 2023
- [c11]Preetam Nandy, Xiufan Yu, Wanjun Liu, Ye Tu, Kinjal Basu, Shaunak Chatterjee:
Generalized Causal Tree for Uplift Modeling. IEEE Big Data 2023: 788-798 - [c10]Cyrus DiCiccio
, Brian Hsu
Detection and Mitigation of Algorithmic Bias via Predictive Parity. FAccT 2023: 1801-1816 - 2022
- [c9]Nil-Jana Akpinar, Cyrus DiCiccio, Preetam Nandy, Kinjal Basu:
Long-term Dynamics of Fairness Intervention in Connection Recommender Systems. AIES 2022: 22-35 - [c8]Yiping Yuan, Ajith Muralidharan, Preetam Nandy, Miao Cheng, Prakruthi Prabhakar:
Offline Reinforcement Learning for Mobile Notifications. CIKM 2022: 3614-3623 - [c7]Preetam Nandy, Cyrus DiCiccio, Divya Venugopalan, Heloise Logan, Kinjal Basu, Noureddine El Karoui:
Achieving Fairness via Post-Processing in Web-Scale Recommender Systems✱. FAccT 2022: 715-725 - [c6]Brian Hsu, Rahul Mazumder, Preetam Nandy, Kinjal Basu:
Pushing the limits of fairness impossibility: Who's the fairest of them all? NeurIPS 2022 - [i5]Yiping Yuan, Ajith Muralidharan, Preetam Nandy, Miao Cheng, Prakruthi Prabhakar:
Offline Reinforcement Learning for Mobile Notifications. CoRR abs/2202.03867 (2022) - [i4]Nil-Jana Akpinar, Cyrus DiCiccio, Preetam Nandy, Kinjal Basu:
Long-term Dynamics of Fairness Intervention in Connection Recommender Systems. CoRR abs/2203.16432 (2022) - [i3]Brian Hsu, Rahul Mazumder, Preetam Nandy, Kinjal Basu:
Pushing the limits of fairness impossibility: Who's the fairest of them all? CoRR abs/2208.12606 (2022) - 2021
- [c5]Preetam Nandy, Divya Venugopalan, Chun Lo, Shaunak Chatterjee:
A/B Testing for Recommender Systems in a Two-sided Marketplace. NeurIPS 2021: 6466-6477 - [c4]Ye Tu, Kinjal Basu, Cyrus DiCiccio, Romil Bansal, Preetam Nandy, Padmini Jaikumar, Shaunak Chatterjee:
Personalized Treatment Selection using Causal Heterogeneity. WWW 2021: 1574-1585 - [i2]Preetam Nandy, Divya Venugopalan, Chun Lo, Shaunak Chatterjee:
A/B Testing for Recommender Systems in a Two-sided Marketplace. CoRR abs/2106.00762 (2021) - 2020
- [c3]Preetam Nandy, Kinjal Basu, Shaunak Chatterjee, Ye Tu:
A/B Testing in Dense Large-Scale Networks: Design and Inference. NeurIPS 2020 - [i1]Preetam Nandy, Amir Sepehri, Kinjal Basu, Heloise Logan, Deepak Agarwal, Noureddine El Karoui:
Scalable Assessment and Mitigation Strategies for Fairness in Rankings. CoRR abs/2006.11350 (2020)
2010 – 2019
- 2017
- [c2]Marco Eigenmann, Preetam Nandy, Marloes H. Maathuis:
Structure Learning of Linear Gaussian Structural Equation Models with Weak Edges. UAI 2017 - 2016
- [p1]Marloes H. Maathuis, Preetam Nandy:
A Review of Some Recent Advances in Causal Inference. Handbook of Big Data 2016: 387-407 - 2013
- [j1]Adi L. Tarca, Mario Lauria
Strengths and limitations of microarray-based phenotype prediction: lessons learned from the IMPROVER Diagnostic Signature Challenge. Bioinform. 29(22): 2892-2899 (2013) - 2012
- [c1]Christoph Zechner
Optimal variational perturbations for the inference of stochastic reaction dynamics. CDC 2012: 5336-5341
Coauthor Index
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