| 2022 |
S. Majumdar, S. Chatterjee.
Feature Selection using e-values, ICML 2022. |
| 2022 |
S. Majumdar, S. Chatterjee.
On weighted multivariate sign functions,
Journal of Multivariate Analysis 191, 105013. |
| 2022 |
Y. Pruksachatkun, M. McAteer, S. Majumdar.
Practicing Trustworthy Machine Learning, published by O'Reilly Media (book).
|
| 2022 |
S. Majumdar.
Fairness, Explainability, Privacy, and Robustness for Trustworthy Algorithmic Decision Making,
In Big Data Analytics in Chemoinformatics and Bioinformatics, published by Elsevier (book chapter, in press).
|
| 2022 |
S. Majumdar, C. Flynn, R. Mitra.
Detecting Bias in the Presence of Spatial Autocorrelation, NeurIPS 2021 AFCR Workshop.
|
| 2022 |
S. Majumdar, G. Michailidis.
Joint Estimation and Inference for Data Integration Problems based on Multiple Multi-layered Gaussian Graphical Models,
Journal of Machine Learning Research 23(1), 1-53.
|
| 2021 |
S. Majumdar, D. Paul, E. Zavesky.
Scaling New Peaks: A Viewership-centric Approach to Automated Content Curation, arXiv:2108.04187.
|
| 2021 |
S. Majumdar, S. Chatterjee.
Generalized Multivariate Signs for Nonparametric Hypothesis Testing in High Dimensions, arXiv:2107.01103.
|
| 2021 |
N. Derzsy*, S. Majumdar*, R. Malik*.
An Interpretable Graph-based Mapping of Trustworthy Machine Learning Research,
CompleNet 2021.
|
| 2021 |
C. Last, P. Pramanik, N. Saini, A.S. Majety, D.-H. Kim, M.-G. Herranz, S. Majumdar.
Towards An Open Global Air Quality Monitoring Platform to Assess Children's Exposure to Air Pollutants in the Light of COVID-19 Lockdowns,
CHI 2021 Late Breaking Work.
|
| 2020 |
V.A.E. Farias, F.T. Brito, C. Flynn, J.C. Machado, S. Majumdar, D. Srivastava.
Local Dampening: Differential Privacy for Non-numeric Queries via Local Sensitivity,
Proceedings of the VLDB Endowment, 14(4), 521-533.
|
| 2020 |
R.M. Rustamov, S. Majumdar.
Intrinsic Sliced Wasserstein Distances for Comparing Collections of Probability Distributions on Manifolds and Graphs, arXiv:2010.15285.
|
| 2020 |
E. Dodwell*, C. Flynn*, B. Krishnamurthy*, S. Majumdar*, R. Mitra*.
Towards Integrating Fairness Transparently in Industrial Applications, arXiv:2006.06082.
|
| 2020 |
S.P. Fookolaee, S. Karkhah, M. Saadi, S. Majumdar, A. Karkhah.
Novel computational approaches to developing potential STAT4 silencing siRNAs for immunomodulation of atherosclerosis,
Current Computer-Aided Drug Design 16 (5), 599-604.
|
| 2020 |
S.C. Basak, S. Majumdar, M. Vracko, A. Nandy, A. Bhattacharjee.
A Generic Computer-Assisted Four-Pronged Approach for the Management of Emerging Global Pathogens: Some Comments on COVID-19,
Current Computer-Aided Drug Design 16 (4), 351-353.
|
| 2020 |
A. Ghosh, S. Majumdar.
Ultrahigh-dimensional Robust and Efficient Sparse Regression using Non-Concave Penalized Density Power Divergence,
IEEE Transactions on Information Theory 66 (12), 7812-7827.
|
| 2019 |
S.C. Basak, S. Majumdar, A. Nandy, P. Roy, T. Dutta, M. Vracko, A.K. Bhattacharjee.
Computer-Assisted and Data Driven Approaches for Surveillance, Drug Discovery, and Vaccine Design for the Zika Virus,
Pharmaceuticals 12 (4), 157.
|
| 2019 |
S. Majumdar, S.C. Basak, C.N. Lungu, M.V. Diudea, G.D. Grunwald.
Finding Needles in a Haystack: Determining Key Molecular Descriptors Associated with the Blood‐brain Barrier Entry of Chemical Compounds Using Machine Learning,
Molecular Informatics 38 (8-9), 1800164.
|
| 2019 |
T. Biswas, T.K. Sabui, R. Mondal, S. Majumdar, S. Misra.
Transpyloric Feed in Gastroesophageal Reflux Assocciated Apnea in Premature Infants: A Prospective Study,
Gastroenterology 156 (6), S-308.
|
| 2019 |
11 authors.
Confronting data sparsity to identify potential sources of Zika virus spillover infection among primates,
Epidemics 27, 59-65.
|
| 2019 |
S. Majumdar.
In Zika Virus Surveillance, Vaccinology, and Anti-Zika Drug Discovery: Computer-Assisted Strategies to Combat the Menace,
published by Nova Science Publishers, pp 129-152 (book chapter).
|
| 2018 |
S. Majumdar, S.C. Basak, C.N. Lungu, M.V. Diudea, G.D. Grunwald.
Mathematical structural descriptors and mutagenicity assessment: a study with congeneric and diverse datasets,
SAR and QSAR in Environmental Research 29 (8), 579-590.
|
| 2018 |
S. Majumdar, S.C. Basak.
Beware of external validation!-A Comparative Study of Several Validation Techniques used in QSAR Modelling,
Current Computer-Aided Drug Design 14 (4), 284-291.
|
| 2018 |
S. Majumdar, S.C. Basak.
Editorial: Beware of Naïve q2, use True q2: Some Comments on QSAR Model Building and Cross Validation,
Current Computer-Aided Drug Design 14 (1), 5-6.
|
| 2018 |
S. Majumdar, S. Basu, M. McGue, S. Chatterjee.
Simultaneous Selection of Multiple Important Single Nucleotide Polymorphisms in Familial Genome Wide Association Studies Data,
arXiv:1802.01141 (
presented in ICML 2021 CompBio workshop).
|
| 2018 |
S. Majumdar, S. Chatterjee.
Non-convex penalized multitask regression using data depth-based penalties, Stat 7, e174.
|
| 2017 |
S. Majumdar, S. Chatterjee.
Fast and General Best Subset Selection using Data Depth and Resampling, arXiv:1706.02429.
|
| 2017 |
T. Biswas, S. Majumdar.
Statistical Methods: Need for a Rethink, Indian Pediatrics 54 (1), 65.
|
| 2016 |
S. Majumdar, S.C. Basak.
Exploring intrinsic dimensionality of chemical spaces for robust QSAR model development: A comparison of several statistical approaches,
Current Computer-Aided Drug Design 12 (4), 294-301.
|
| 2016 |
S. Majumdar, S.C. Basak.
EDITORIAL: Chemodescriptor Based QSARs of Structurally Homogeneous Versus Heterogeneous Chemical Data Sets: Some Comments on the Congenericity Principle
vis-à-vis Diversity Begets Diversity Principle, Current Computer-Aided Drug Design 12 (4), 84-86.
|
| 2015 |
S. Majumdar, L.R. Dietz, S. Chatterjee.
Identifying Driving Factors Behind Indian Monsoon Precipitation using Model Selection based on Data Depth,
Proceedings of the Fifth International Workshop on Climate Informatics: CI 2015.
|
| 2015 |
S.C. Basak, S. Majumdar.
Prediction of Mutagenicity of Chemicals from Their Calculated Molecular Descriptors: A Case Study with Structurally Homogeneous versus Diverse Datasets,
Current Computer-Aided Drug Design 11 (2), 117-123.
|
| 2015 |
10 authors.
Predictive Modeling for Public Health: Preventing Childhood Lead Poisoning, KDD 2015.
|
| 2015 |
U.K. Mukherjee, S. Majumdar, S. Chatterjee.
Fast and robust supervised learning in high dimensions using the geometry of the data, ICDM 2015.
|
| 2015 |
S.C. Basak, S. Majumdar.
Editorial: The Importance of Rigorous Statistical Practice in the Current Landscape of QSAR Modelling,
Current Computer-Aided Drug Design 11 (1), 2-4.
|
| 2015 |
S.C. Basak, S. Majumdar.
Current landscape of hierarchical QSAR modeling and its applications: Some comments on the importance of mathematical descriptors as well as
rigorous statistical methods of model building and validation,
In Advances in mathematical chemistry and applications, published by Bentham Science Publishers, pp 251-281 (book chapter).
|
| 2013 |
S. Majumdar, S.C. Basak, G.D.Grunwald.
Adapting Interrelated Two-Way Clustering Method for Quantitative Structure-Activity Relationship (QSAR) Modeling of Mutagenicity/Non-Mutagenicity of a Diverse Set of Chemicals,
Current Computer-Aided Drug Design 9 (4), 463-471.
|