Preetam Nandy
Title
Cited by
Cited by
Year
Strengths and limitations of microarray-based phenotype prediction: lessons learned from the IMPROVER Diagnostic Signature Challenge
AL Tarca, M Lauria, M Unger, E Bilal, S Boue, K Kumar Dey, J Hoeng, ...
Bioinformatics 29 (22), 2892-2899, 2013
982013
High-dimensional consistency in score-based and hybrid structure learning
P Nandy, A Hauser, MH Maathuis
The Annals of Statistics 46 (6A), 3151-3183, 2018
522018
Estimating the effect of joint interventions from observational data in sparse high-dimensional settings
P Nandy, MH Maathuis, TS Richardson
The Annals of Statistics 45 (2), 647-674, 2017
332017
A Review of Some Recent Advances in Causal Inference
MH Maathuis, P Nandy
Handbook of Big Data, 387-407, 2016
272016
Large-sample theory for the Bergsma-Dassios sign covariance
P Nandy, L Weihs, M Drton
Electronic Journal of Statistics 10 (2), 2287-2311, 2016
102016
Robust causal structure learning with some hidden variables
B Frot, P Nandy, MH Maathuis
arXiv preprint arXiv:1708.01151, 2017
9*2017
Optimal variational perturbations for the inference of stochastic reaction dynamics
C Zechner, P Nandy, M Unger, H Koeppl
2012 IEEE 51st IEEE conference on decision and control (CDC), 5336-5341, 2012
92012
Package ‘pcalg’
M Kalisch, A Hauser, M Maechler, D Colombo, D Entner, P Hoyer, ...
7*2020
Structure learning of linear gaussian structural equation models with weak edges
MF Eigenmann, P Nandy, MH Maathuis
arXiv preprint arXiv:1707.07560, 2017
72017
Optimal perturbations for the identification of stochastic reaction dynamics
P Nandy, M Unger, C Zechner, H Koeppl
IFAC Proceedings Volumes 45 (16), 686-691, 2012
62012
Learning diagnostic signatures from microarray data using L1-regularized logistic regression
P Nandy, M Unger, C Zechner, KK Dey, H Koeppl
Systems Biomedicine 1 (4), 240-246, 2013
42013
A/B Testing in Dense Large-Scale Networks: Design and Inference
P Nandy, K Basu, S Chatterjee, Y Tu
arXiv preprint arXiv:1901.10505, 2019
32019
Inference for Individual Mediation Effects and Interventional Effects in Sparse High-Dimensional Causal Graphical Models
A Chakrabortty, P Nandy, H Li
arXiv preprint arXiv:1809.10652, 2018
32018
Optimal convergence for stochastic optimization with multiple expectation constraints
K Basu, P Nandy
arXiv preprint arXiv:1906.03401, 2019
22019
Scalable Assessment and Mitigation Strategies for Fairness in Rankings
P Nandy, A Sepehri, K Basu, H Logan, D Agarwal, NE Karoui
arXiv preprint arXiv:2006.11350, 2020
2020
Causal learning from high-dimensional observational data
P Nandy
ETH Zurich, 2016
2016
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Articles 1–16