Subhabrata Majumdar

38 papers A* 5C 1Journal 27Unranked 5
YearRankTypeTitle / Venue / Authors
2026 J jnl
Limits of Convergence-Rate Control for Open-Weight Safety.
CoRR
Domenic Rosati, Xijie Zeng, Hong Huang, Sebastian Dionicio, Subhabrata Majumdar, Frank Rudzicz, Hassan Sajjad
2025 J jnl
Consistency in Language Models: Current Landscape, Challenges, and Future Directions.
CoRR
Jekaterina Novikova, Carol Anderson, Borhane Blili-Hamelin, Subhabrata Majumdar
2025 J jnl
Exploring AI ethics in global contexts: a culturally responsive, psychologically realist approach.
AI Ethics
Rockwell F. Clancy, Qin Zhu, Subhabrata Majumdar
2025 J jnl
Improving Consistency in Large Language Models through Chain of Guidance.
CoRR
Harsh Raj, Vipul Gupta, Domenic Rosati, Subhabrata Majumdar
2025 J jnl
Improving Consistency in Large Language Models through Chain of Guidance.
Trans. Mach. Learn. Res.
Harsh Raj, Vipul Gupta, Domenic Rosati, Subhabrata Majumdar
2025 C conf
Localized LoRA: A Structured Low-Rank Approximation for Efficient Fine-Tuning.
ICMLA
Babak Barazandeh, Subhabrata Majumdar, Om Rajyaguru, George Michailidis
2025 — conf
Red Teaming AI Red Teaming.
CAMLIS
Subhabrata Majumdar, Brian Pendleton, Abhishek Gupta
2025 J jnl
Red Teaming AI Red Teaming.
CoRR
Subhabrata Majumdar, Brian Pendleton, Abhishek Gupta
2024 J jnl
Defending against Reverse Preference Attacks is Difficult.
CoRR
Domenic Rosati, Giles Edkins, Harsh Raj, David Atanasov, Subhabrata Majumdar, Janarthanan Rajendran, Frank Rudzicz, Hassan Sajjad
2024 — conf
Embedding-based classifiers can detect prompt injection attacks.
CAMLIS
Md. Ahsan Ayub, Subhabrata Majumdar
2024 J jnl
Embedding-based classifiers can detect prompt injection attacks.
CoRR
Md. Ahsan Ayub, Subhabrata Majumdar
2024 A* conf
Representation Noising: A Defence Mechanism Against Harmful Finetuning.
NeurIPS
Domenic Rosati, Jan Wehner, Kai Williams, Lukasz Bartoszcze, Robie Gonzales, Carsten Maple, Subhabrata Majumdar, Hassan Sajjad, Frank Rudzicz
2024 J jnl
Representation noising effectively prevents harmful fine-tuning on LLMs.
CoRR
Domenic Rosati, Jan Wehner, Kai Williams, Lukasz Bartoszcze, David Atanasov, Robie Gonzales, Subhabrata Majumdar, Carsten Maple, Hassan Sajjad, Frank Rudzicz
2023 J jnl
Global and Local Differentially Private Release of Count-Weighted Graphs.
Proc. ACM Manag. Data
Felipe T. Brito, Victor A. E. de Farias, Cheryl J. Flynn, Subhabrata Majumdar, Javam C. Machado, Divesh Srivastava
2023 A* conf
Intrinsic Sliced Wasserstein Distances for Comparing Collections of Probability Distributions on Manifolds and Graphs.
ICML
Raif M. Rustamov, Subhabrata Majumdar
2023 J jnl
Local dampening: differential privacy for non-numeric queries via local sensitivity.
VLDB J.
Victor A. E. de Farias, Felipe T. Brito, Cheryl J. Flynn, Javam C. Machado, Subhabrata Majumdar, Divesh Srivastava
2023 J jnl
Semantic Consistency for Assuring Reliability of Large Language Models.
CoRR
Harsh Raj, Vipul Gupta, Domenic Rosati, Subhabrata Majumdar
2022 J jnl
Feature Selection using e-values.
CoRR
Subhabrata Majumdar, Snigdhansu Chatterjee
2022 A* conf
Feature selection using e-values.
ICML
Subhabrata Majumdar, Snigdhansu Chatterjee
2022 J jnl
Joint Estimation and Inference for Data Integration Problems based on Multiple Multi-layered Gaussian Graphical Models.
J. Mach. Learn. Res.
Subhabrata Majumdar, George Michailidis
2022 J jnl
Measuring Reliability of Large Language Models through Semantic Consistency.
CoRR
Harsh Raj, Domenic Rosati, Subhabrata Majumdar
2022 — conf
Network Security Modelling with Distributional Data.
CAMLIS
Subhabrata Majumdar, Ganesh Subramaniam
2022 J jnl
Network Security Modelling with Distributional Data.
CoRR
Subhabrata Majumdar, Ganesh Subramaniam
2022 J jnl
On weighted multivariate sign functions.
J. Multivar. Anal.
Subhabrata Majumdar, Snigdhansu Chatterjee
2022 J jnl
Towards Algorithmic Fairness in Space-Time: Filling in Black Holes.
CoRR
Cheryl J. Flynn, Aritra Guha, Subhabrata Majumdar, Divesh Srivastava, Zhengyi Zhou
2021 J jnl
An Interpretable Graph-based Mapping of Trustworthy Machine Learning Research.
CoRR
Noemi Derzsy, Subhabrata Majumdar, Rajat Malik
2021 — conf
Detecting Bias in the Presence of Spatial Autocorrelation.
AFCR
Subhabrata Majumdar, Cheryl J. Flynn, Ritwik Mitra
2021 J jnl
Evaluating Fairness in the Presence of Spatial Autocorrelation.
CoRR
Cheryl J. Flynn, Subhabrata Majumdar, Ritwik Mitra
2021 J jnl
Generalized Multivariate Signs for Nonparametric Hypothesis Testing in High Dimensions.
CoRR
Subhabrata Majumdar, Snigdhansu Chatterjee
2021 J jnl
Scaling New Peaks: A Viewership-centric Approach to Automated Content Curation.
CoRR
Subhabrata Majumdar, Deirdre Paul, Eric Zavesky
2021 — conf
Towards an Open Global Air Quality Monitoring Platform to Assess Children's Exposure to Air Pollutants in the Light of COVID-19 Lockdowns.
CHI Extended Abstracts
Christina Last, Prithviraj Pramanik, Nikita Saini, Akash Smaran Majety, Do-Hyung Kim, Manuel García-Herranz, Subhabrata Majumdar
2021 J jnl
Towards an Open Global Air Quality Monitoring Platform to Assess Children's Exposure to Air Pollutants in the Light of COVID-19 Lockdowns.
CoRR
Christina Last, Prithviraj Pramanik, Nikita Saini, Akash Smaran Majety, Do-Hyung Kim, Manuel García-Herranz, Subhabrata Majumdar
2020 J jnl
Local Dampening: Differential Privacy for Non-numeric Queries via Local Sensitivity.
CoRR
Victor A. E. de Farias, Felipe T. Brito, Cheryl J. Flynn, Javam C. Machado, Subhabrata Majumdar, Divesh Srivastava
2020 J jnl
Local Dampening: Differential Privacy for Non-numeric Queries via Local Sensitivity.
Proc. VLDB Endow.
Victor A. E. de Farias, Felipe T. Brito, Cheryl J. Flynn, Javam C. Machado, Subhabrata Majumdar, Divesh Srivastava
2020 J jnl
System to Integrate Fairness Transparently: An Industry Approach.
CoRR
Emily Dodwell, Cheryl J. Flynn, Balachander Krishnamurthy, Subhabrata Majumdar, Ritwik Mitra
2020 J jnl
Ultrahigh-Dimensional Robust and Efficient Sparse Regression Using Non-Concave Penalized Density Power Divergence.
IEEE Trans. Inf. Theory
Abhik Ghosh, Subhabrata Majumdar
2015 A* conf
Fast and Robust Supervised Learning in High Dimensions Using the Geometry of the Data.
ICDM
Ujjal Kumar Mukherjee, Subhabrata Majumdar, Snigdhansu Chatterjee
2015 A* conf
Predictive Modeling for Public Health: Preventing Childhood Lead Poisoning.
KDD
Eric Potash, Joe Brew, Alexander Loewi, Subhabrata Majumdar, Andrew Reece, Joe Walsh, Eric Rozier, Emile Jorgenson, Raed Mansour, Rayid Ghani