Subhabrata Majumdar

According to our database, Subhabrata Majumdar authored at least 20 papers between 2015 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Global and Local Differentially Private Release of Count-Weighted Graphs.

Felipe T. Brito, Victor A. E. de Farias, Cheryl J. Flynn, Subhabrata Majumdar, Javam C. Machado, Divesh Srivastava

Proc. ACM Manag. Data, 2023

Semantic Consistency for Assuring Reliability of Large Language Models.

Harsh Raj, Vipul Gupta, Domenic Rosati, Subhabrata Majumdar

CoRR, 2023

Intrinsic Sliced Wasserstein Distances for Comparing Collections of Probability Distributions on Manifolds and Graphs.

Raif M. Rustamov, Subhabrata Majumdar

Proceedings of the International Conference on Machine Learning, 2023

2022

On weighted multivariate sign functions.

Subhabrata Majumdar, Snigdhansu Chatterjee

J. Multivar. Anal., 2022

Joint Estimation and Inference for Data Integration Problems based on Multiple Multi-layered Gaussian Graphical Models.

Subhabrata Majumdar, George Michailidis

J. Mach. Learn. Res., 2022

Measuring Reliability of Large Language Models through Semantic Consistency.

Harsh Raj, Domenic Rosati, Subhabrata Majumdar

CoRR, 2022

Towards Algorithmic Fairness in Space-Time: Filling in Black Holes.

Cheryl J. Flynn, Aritra Guha, Subhabrata Majumdar, Divesh Srivastava, Zhengyi Zhou

CoRR, 2022

Feature selection using e-values.

Subhabrata Majumdar, Snigdhansu Chatterjee

Proceedings of the International Conference on Machine Learning, 2022

Network Security Modelling with Distributional Data.

Subhabrata Majumdar, Ganesh Subramaniam

Proceedings of the Conference on Applied Machine Learning in Information Security, 2022

2021

Scaling New Peaks: A Viewership-centric Approach to Automated Content Curation.

Subhabrata Majumdar, Deirdre Paul, Eric Zavesky

CoRR, 2021

Generalized Multivariate Signs for Nonparametric Hypothesis Testing in High Dimensions.

Subhabrata Majumdar, Snigdhansu Chatterjee

CoRR, 2021

An Interpretable Graph-based Mapping of Trustworthy Machine Learning Research.

Noemi Derzsy, Subhabrata Majumdar, Rajat Malik

CoRR, 2021

Evaluating Fairness in the Presence of Spatial Autocorrelation.

Cheryl J. Flynn, Subhabrata Majumdar, Ritwik Mitra

CoRR, 2021

Towards an Open Global Air Quality Monitoring Platform to Assess Children's Exposure to Air Pollutants in the Light of COVID-19 Lockdowns.

Christina Last, Prithviraj Pramanik, Nikita Saini, Akash Smaran Majety, Do-Hyung Kim, Manuel García-Herranz, Subhabrata Majumdar

Proceedings of the CHI '21: CHI Conference on Human Factors in Computing Systems, 2021

Detecting Bias in the Presence of Spatial Autocorrelation.

Subhabrata Majumdar, Cheryl J. Flynn, Ritwik Mitra

Proceedings of the Algorithmic Fairness through the Lens of Causality and Robustness Workshop, 2021

2020

Ultrahigh-Dimensional Robust and Efficient Sparse Regression Using Non-Concave Penalized Density Power Divergence.

Abhik Ghosh, Subhabrata Majumdar

IEEE Trans. Inf. Theory, 2020

Local Dampening: Differential Privacy for Non-numeric Queries via Local Sensitivity.

Victor A. E. de Farias, Felipe T. Brito, Cheryl J. Flynn, Javam C. Machado, Subhabrata Majumdar, Divesh Srivastava

Proc. VLDB Endow., 2020

System to Integrate Fairness Transparently: An Industry Approach.

Emily Dodwell, Cheryl J. Flynn, Balachander Krishnamurthy, Subhabrata Majumdar, Ritwik Mitra

CoRR, 2020

2015

Predictive Modeling for Public Health: Preventing Childhood Lead Poisoning.

Eric Potash, Joe Brew, Alexander Loewi, Subhabrata Majumdar, Andrew Reece, Joe Walsh, Eric Rozier, Emile Jorgenson, Raed Mansour, Rayid Ghani

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Fast and Robust Supervised Learning in High Dimensions Using the Geometry of the Data.

Ujjal Kumar Mukherjee, Subhabrata Majumdar, Snigdhansu Chatterjee

Proceedings of the Advances in Data Mining: Applications and Theoretical Aspects, 2015