2 papers
cs.LG2026
Quantifying the Value of Privileged Information Using a PAC-Bayesian Approach
Vasily Bokov, Sebastian Schmitt, Vedran Dunjko +1
In practice, various learning scenarios provide access to auxiliary features exclusively during training. Incorporating such data to enhance model performance gave rise to a paradi…
quant-ph2026
Machine learning with minimal use of quantum computers: Provable advantages in Learning Under Quantum Privileged Information (LUQPI)
Vasily Bokov, Lisa Kohl, Sebastian Schmitt +1
Quantum machine learning (QML) is often listed as a promising candidate for useful applications of quantum computers, in part due to numerous proofs of possible quantum advantages.…