Author

Heranga K. Rathnasekara

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#artificial intelligence Preprint Aug 2026

Magnitude Profile Pruning: Calibration-Free Structured Attention Head Removal for Transformer Compression

Structured pruning of attention heads provides a hardware-friendly way to compress Transformer language models. However, existing methods for measuring head-level importance require calibration data, gradient computation, or Hessian estimation. These requirements add extra overhead and make the methods depend on the da...

Kasun Dewage, Marianna Pensky, Heranga K. Rathnasekara et al. · 0 citations

#machine learning Preprint Sep 2026

Copula Adapted Directed Acyclic Graph for Cluster Representation of Biomedical Data

Diagnostic errors and mislabeling are common in biomedicine, which compromise the reliability of predictive models and data-driven outcomes. Stratifying unlabeled biomedical data based on complex relationships between features eliminates the need for data labels and overcomes the limitations of supervised learning. Tra...

Heranga K. Rathnasekara, N. Diawara, Manar D. Samad · 0 citations