1 citations · 2 across the 14 of their papers we have counts for
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Limits of quantum generative models with classical sampling hardness
Sabrina Herbst, Ivona Brandić, Adrián Pérez-Salinas
Sampling tasks have been successful in establishing quantum advantages both in theory and experiments. This has fueled the use of quantum computers for generative modeling to creat…
Clustered Federated Learning with Hierarchical Knowledge Distillation
Sabtain Ahmad, Meerzhan Kanatbekova, Ivona Brandic +1
Clustered Federated Learning (CFL) has emerged as a powerful approach for addressing data heterogeneity and ensuring privacy in large distributed IoT environments. By clustering cl…
Qubit-Efficient QUBO Formulation for Constrained Optimization Problems
Meerzhan Kanatbekova, Vincenzo De Maio, Ivona Brandic
Quantum computing has emerged as a promising alternative for solving combinatorial optimization problems. The standard approach for encoding optimization problems on quantum proces…
Breaking Down Quantum Compilation: Profiling and Identifying Costly Passes
Felix Zilk, Alessandro Tundo, Vincenzo De Maio +1
With the increasing capabilities of quantum systems, the efficient, practical execution of quantum programs is becoming more critical. Each execution includes compilation time, whi…
The Road to Hybrid Quantum Programs: Characterizing the Evolution from Classical to Hybrid Quantum Software
Vincenzo De Maio, Ivona Brandic, Ewa Deelman +1
Quantum computing exhibits the unique capability to natively and efficiently encode various natural phenomena, promising theoretical speedups of several orders of magnitude. Howeve…
GREEN-CODE: Learning to Optimize Energy Efficiency in LLM-based Code Generation
Shashikant Ilager, Lukas Florian Briem, Ivona Brandic
Large Language Models (LLMs) are becoming integral to daily life, showcasing their vast potential across various Natural Language Processing (NLP) tasks. Beyond NLP, LLMs are incre…