Preetam Nandy

Publication Activity (10 Years)

Years Active: 2012-2023
Publications (10 Years): 15

Top Topics

Reinforcement Learning

Recommender Systems

Matrix Factorization

Top Venues

Publications

Cyrus DiCiccio, Brian Hsu, YinYin Yu, Preetam Nandy, Kinjal Basu
Detection and Mitigation of Algorithmic Bias via Predictive Parity. FAccT (2023)
Preetam Nandy, Xiufan Yu, Wanjun Liu, Ye Tu, Kinjal Basu, Shaunak Chatterjee
Generalized Causal Tree for Uplift Modeling. BigData (2023)
Brian Hsu, Rahul Mazumder, Preetam Nandy, Kinjal Basu
Pushing the limits of fairness impossibility: Who's the fairest of them all? CoRR (2022)
Brian Hsu, Rahul Mazumder, Preetam Nandy, Kinjal Basu
Pushing the limits of fairness impossibility: Who's the fairest of them all? NeurIPS (2022)
Yiping Yuan, Ajith Muralidharan, Preetam Nandy, Miao Cheng, Prakruthi Prabhakar
Offline Reinforcement Learning for Mobile Notifications. CIKM (2022)
Nil-Jana Akpinar, Cyrus DiCiccio, Preetam Nandy, Kinjal Basu
Long-term Dynamics of Fairness Intervention in Connection Recommender Systems. CoRR (2022)
Yiping Yuan, Ajith Muralidharan, Preetam Nandy, Miao Cheng, Prakruthi Prabhakar
Offline Reinforcement Learning for Mobile Notifications. CoRR (2022)
Nil-Jana Akpinar, Cyrus DiCiccio, Preetam Nandy, Kinjal Basu
Long-term Dynamics of Fairness Intervention in Connection Recommender Systems. AIES (2022)
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)
Preetam Nandy, Divya Venugopalan, Chun Lo, Shaunak Chatterjee
A/B Testing for Recommender Systems in a Two-sided Marketplace. CoRR (2021)
Ye Tu, Kinjal Basu, Cyrus DiCiccio, Romil Bansal, Preetam Nandy, Padmini Jaikumar, Shaunak Chatterjee
Personalized Treatment Selection using Causal Heterogeneity. WWW (2021)
Preetam Nandy, Divya Venugopalan, Chun Lo, Shaunak Chatterjee
A/B Testing for Recommender Systems in a Two-sided Marketplace. NeurIPS (2021)
Preetam Nandy, Kinjal Basu, Shaunak Chatterjee, Ye Tu
A/B Testing in Dense Large-Scale Networks: Design and Inference. NeurIPS (2020)
Preetam Nandy, Amir Sepehri, Kinjal Basu, Heloise Logan, Deepak Agarwal, Noureddine El Karoui
Scalable Assessment and Mitigation Strategies for Fairness in Rankings. CoRR (2020)
Marco Eigenmann, Preetam Nandy, Marloes H. Maathuis
Structure Learning of Linear Gaussian Structural Equation Models with Weak Edges. UAI (2017)
Adi L. Tarca, Mario Lauria, Michael Unger, Erhan Bilal, Stéphanie Boué, Kushal Kumar Dey, Julia Hoeng, Heinz Koeppl, Florian Martin, Pablo Meyer, Preetam Nandy, Raquel Norel, Manuel C. Peitsch, John Jeremy Rice, Roberto Romero, Gustavo Stolovitzky, Marja Talikka, Yang Xiang, Christoph Zechner, Improver Dsc Collaborators
Strengths and limitations of microarray-based phenotype prediction: lessons learned from the IMPROVER Diagnostic Signature Challenge. Bioinform. 29 (22) (2013)
Christoph Zechner, Preetam Nandy, Michael Unger, Heinz Koeppl
Optimal variational perturbations for the inference of stochastic reaction dynamics. CDC (2012)