Author

Rahul Mazumder

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#artificial intelligence Preprint Oct 2026

Reconstruction-Optimized Expert Pruning for Mixture-of-Experts Language Models

OptEP is developed, a scalable continuous relaxation that directly optimizes differentiable expert-selection variables, followed by a lightweight reconstruction-based update of the retained expert weights, demonstrating that reconstruction-driven expert selection and weight adaptation can preserve substantially more of...

Jelena Markovic-Voronov, P. Prastakos, Kayhan Behdin et al. · 0 citations

#artificial intelligence Preprint Sep 2026

ThinQuant: Scalable Rotation Learning for Weight and Activation Quantization of LLMs

ThinQuant is introduced, a data selection procedure which reduces the required number of calibration data points and an exact reduction of the associated optimization on this reduced calibration set using an efficient ADMM algorithm that iteratively employs thin matrix updates at every step, hence the name ThinQuant.

Mehdi Makni, Ryan Lucas, R. Mazumder · 0 citations

Open access Sep 2026

SPLENDID incorporates continuous genetic ancestry in biobank-scale data to improve polygenic risk prediction across diverse populations

It is shown that SPLENDID significantly improved prediction accuracy over existing methods, particularly for non-European and admixed ancestries, particularly for non-European and admixed ancestries.

Tony Chen, Hao-Yu Zhang, R. Mazumder et al. · Nature Methods · 0 citations