5 papers
Privacy Implies Stability: Information-Theoretic Generalization Bounds for Quantum Learning
Ayanava Dasgupta, Naqueeb Ahmad Warsi, Masahito Hayashi
We develop an information-theoretic framework connecting stability, privacy, and generalization for quantum learning algorithms. Learning procedures are modeled as quantum instrume…
Quantum Information Ordering and Differential Privacy
Naqueeb Ahmad Warsi, Ayanava Dasgupta, Masahito Hayashi
We study quantum differential privacy (QDP) by defining a notion of the order of informativeness between pairs of quantum states. In particular, we show that if the hypothesis test…
Generalization Bounds for Quantum Learning via Rényi Divergences
Naqueeb Ahmad Warsi, Ayanava Dasgupta, Masahito Hayashi
This work advances the theoretical understanding of quantum learning by establishing a new family of upper bounds on the expected generalization error of quantum learning algorithm…
Predicting symmetries of quantum dynamics with optimal samples
Masahito Hayashi, Yu-Ao Chen, Chenghong Zhu +1
Identifying symmetries in quantum dynamics, such as identity or time-reversal invariance, is a crucial challenge with profound implications for quantum technologies. We introduce a…
Universal tester for multiple independence testing and classical-quantum arbitrarily varying multiple access channel
Ayanava Dasgupta, Naqueeb Ahmad Warsi, Masahito Hayashi
We study two kinds of different problems. One is the multiple independence testing, which can be considered as a kind of generalization of quantum Stein's lemma. We test whether th…