most citedTextual analysis of End User License Agreement for red-flagging potentially malicious software

3 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2025

Technical note on Fisher Information for Robust Federated Cross-Validation

Behraj Khan, Tahir Qasim Syed

When training data are fragmented across batches or federated-learned across different geographic locations, trained models manifest performance degradation. That degradation partl…

cs.LG2025

Adapting to Fragmented and Evolving Data: A Fisher Information Perspective

Behraj Khan, Tahir Qasim Syed, Nouman Muhammad Durrani

Modern machine learning systems operating in dynamic environments often face \textit{sequential covariate shift} (SCS), where input distributions evolve over time while the conditi…

cs.IR2025

An agentic system with reinforcement-learned subsystem improvements for parsing form-like documents

Ayesha Amjad, Saurav Sthapit, Tahir Qasim Syed

Extracting alphanumeric data from form-like documents such as invoices, purchase orders, bills, and financial documents is often performed via vision (OCR) and learning algorithms…

cs.LG2024

Mitigating covariate shift in non-colocated data with learned parameter priors

Behraj Khan, Behroz Mirza, Nouman Durrani +1

When training data are distributed across{ time or space,} covariate shift across fragments of training data biases cross-validation, compromising model selection and assessment. W…

cs.SE20243 cited

Textual analysis of End User License Agreement for red-flagging potentially malicious software

Behraj Khan, Tahir Syed, Zeshan Khan +1

New software and updates are downloaded by end users every day. Each dowloaded software has associated with it an End Users License Agreements (EULA), but this is rarely read. An E…