3 papers
cs.LG2025
Representation Learning Preserving Ignorability and Covariate Matching for Treatment Effects
Praharsh Nanavati, Ranjitha Prasad, Karthikeyan Shanmugam
Estimating treatment effects from observational data is challenging due to two main reasons: (a) hidden confounding, and (b) covariate mismatch (control and treatment groups not ha…
cs.CR2024
On Homomorphic Encryption Based Strategies for Class Imbalance in Federated Learning
Arpit Guleria, J. Harshan, Ranjitha Prasad +1
Class imbalance in training datasets can lead to bias and poor generalization in machine learning models. While pre-processing of training datasets can efficiently address both the…
cs.IT2023
Seeing is Believing: A Federated Learning Based Prototype to Detect Wireless Injection Attacks
Aadil Hussain, Nitheesh Gundapu, Sarang Drugkar +3
Reactive injection attacks are a class of security threats in wireless networks wherein adversaries opportunistically inject spoofing packets in the frequency band of a client ther…