28 citations · 58 across the 8 of their papers we have counts for
8 papers · 1 filter
Exploiting Context for Robustness to Label Noise in Active Learning
Sudipta Paul, Shivkumar Chandrasekaran, B. S. Manjunath +1
Several works in computer vision have demonstrated the effectiveness of active learning for adapting the recognition model when new unlabeled data becomes available. Most of these…
FLaPS: Federated Learning and Privately Scaling
Sudipta Paul, Poushali Sengupta, Subhankar Mishra
Federated learning (FL) is a distributed learning process where the model (weights and checkpoints) is transferred to the devices that posses data rather than the classical way of…
LAC : LSTM AUTOENCODER with Community for Insider Threat Detection
Sudipta Paul, Subhankar Mishra
The employees of any organization, institute, or industry, spend a significant amount of time on a computer network, where they develop their own routine of activities in the form…
Text-based Localization of Moments in a Video Corpus
Sudipta Paul, Niluthpol Chowdhury Mithun, Amit K. Roy-Chowdhury
Prior works on text-based video moment localization focus on temporally grounding the textual query in an untrimmed video. These works assume that the relevant video is already kno…
Connecting the Dots: Detecting Adversarial Perturbations Using Context Inconsistency
Shasha Li, Shitong Zhu, Sudipta Paul +5
There has been a recent surge in research on adversarial perturbations that defeat Deep Neural Networks (DNNs) in machine vision; most of these perturbation-based attacks target ob…
Learning With Differential Privacy
Poushali Sengupta, Sudipta Paul, Subhankar Mishra
The leakage of data might have been an extreme effect on the personal level if it contains sensitive information. Common prevention methods like encryption-decryption, endpoint pro…
BUDS: Balancing Utility and Differential Privacy by Shuffling
Poushali Sengupta, Sudipta Paul, Subhankar Mishra
Balancing utility and differential privacy by shuffling or \textit{BUDS} is an approach towards crowd-sourced, statistical databases, with strong privacy and utility balance using…
ARA : Aggregated RAPPOR and Analysis for Centralized Differential Privacy
Sudipta Paul, Subhankar Mishra
Differential privacy(DP) has now become a standard in case of sensitive statistical data analysis. The two main approaches in DP is local and central. Both the approaches have a cl…