Author

Mohammad Saidur Rahman

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#machine learning Preprint Oct 2026

Toward Joint Optimization of Circuit Depth and Training Data Size in Adaptively Grown Quantum Classifiers

Building a quantum model involves a tradeoff: how complex the circuit should be, and how much training data it needs. Caro et al. show that models with fewer trainable gates need less training data to generalize well. Q-FLAIR shows that a quantum feature-map circuit can be grown gate-by-gate, stopping once further grow...

Saeefa Rubaiyet Nowmi, Md Mahmuduzzaman Kamol, Mohammad Saidur Rahman · 0 citations

#artificial intelligence Preprint Sep 2026

A Large-Scale Benchmark and Risk Assessment of Traffic Analysis Attacks on Cloud LLM Services

This work presents, to its knowledge, the first unified measurement study and public benchmark of encrypted LLM traffic across both user--LLM and multi-agent executions, and assess the risk of traffic analysis attack by characterizing traffic signatures, identifying the features most associated with leakage, and testin...

Shahrooz Pouryousef, J. Lopez, Saeefa Rubaiyat Nowmi et al. · 1 citation · ⚡1