2 papers
quant-ph2026
Optimal algorithmic complexity of inference in quantum kernel methods
Elies Gil-Fuster, Seongwook Shin, Sofiene Jerbi +2
Quantum kernel methods are among the leading candidates for achieving quantum advantage in supervised learning. A key bottleneck is the cost of inference: evaluating a trained mode…
quant-ph2024
An unconditional distribution learning advantage with shallow quantum circuits
N. Pirnay, S. Jerbi, J. -P. Seifert +1
One of the core challenges of research in quantum computing is concerned with the question whether quantum advantages can be found for near-term quantum circuits that have implicat…