6 citations · 17 across the 12 of their papers we have counts for
12 papers
DAD++: Improved Data-free Test Time Adversarial Defense
Gaurav Kumar Nayak, Inder Khatri, Shubham Randive +2
With the increasing deployment of deep neural networks in safety-critical applications such as self-driving cars, medical imaging, anomaly detection, etc., adversarial robustness h…
Adversarial Adaptation for French Named Entity Recognition
Arjun Choudhry, Inder Khatri, Pankaj Gupta +4
Named Entity Recognition (NER) is the task of identifying and classifying named entities in large-scale texts into predefined classes. NER in French and other relatively limited-re…
An Emotion-Aware Multi-Task Approach to Fake News and Rumour Detection using Transfer Learning
Arjun Choudhry, Inder Khatri, Minni Jain +1
Social networking sites, blogs, and online articles are instant sources of news for internet users globally. However, in the absence of strict regulations mandating the genuineness…
Transformer-Based Named Entity Recognition for French Using Adversarial Adaptation to Similar Domain Corpora
Arjun Choudhry, Pankaj Gupta, Inder Khatri +4
Named Entity Recognition (NER) involves the identification and classification of named entities in unstructured text into predefined classes. NER in languages with limited resource…
CKS: A Community-based K-shell Decomposition Approach using Community Bridge Nodes for Influence Maximization
Inder Khatri, Aaryan Gupta, Arjun Choudhry +3
Social networks have enabled user-specific advertisements and recommendations on their platforms, which puts a significant focus on Influence Maximisation (IM) for target advertisi…
An Emotion-guided Approach to Domain Adaptive Fake News Detection using Adversarial Learning
Arkajyoti Chakraborty, Inder Khatri, Arjun Choudhry +3
Recent works on fake news detection have shown the efficacy of using emotions as a feature for improved performance. However, the cross-domain impact of emotion-guided features for…
Emotion-guided Cross-domain Fake News Detection using Adversarial Domain Adaptation
Arjun Choudhry, Inder Khatri, Arkajyoti Chakraborty +2
Recent works on fake news detection have shown the efficacy of using emotions as a feature or emotions-based features for improved performance. However, the impact of these emotion…
MCD: A Modified Community Diversity Approach for Detecting Influential Nodes in Social Networks
Aaryan Gupta, Inder Khatri, Arjun Choudhry +1
Over the last couple of decades, Social Networks have connected people on the web from across the globe and have become a crucial part of our daily life. These networks have also r…
Influence Maximization in Social Networks using Discretized Harris Hawks Optimization Algorithm and Neighbour Scout Strategy
Inder Khatri, Arjun Choudhry, Aryaman Rao +3
Influence Maximization (IM) is the task of determining k optimal influential nodes in a social network to maximize the influence spread using a propagation model. IM is a prominent…
A Spreader Ranking Algorithm for Extremely Low-budget Influence Maximization in Social Networks using Community Bridge Nodes
Aaryan Gupta, Inder Khatri, Arjun Choudhry +3
In recent years, social networking platforms have gained significant popularity among the masses like connecting with people and propagating ones thoughts and opinions. This has op…
Robust Few-shot Learning Without Using any Adversarial Samples
Gaurav Kumar Nayak, Ruchit Rawal, Inder Khatri +1
The high cost of acquiring and annotating samples has made the `few-shot' learning problem of prime importance. Existing works mainly focus on improving performance on clean data a…
Data-free Defense of Black Box Models Against Adversarial Attacks
Gaurav Kumar Nayak, Inder Khatri, Ruchit Rawal +1
Several companies often safeguard their trained deep models (i.e., details of architecture, learnt weights, training details etc.) from third-party users by exposing them only as b…