Solving optimization problems is a key task for which quantum computers could possibly provide a speedup over the best known classical algorithms. Particular classes of optimization problems including semidefinite programming (SDP) and linear programming ( ...
Secure multi-party computation enables a group of parties to compute a function while jointly keeping their private inputs secret. The term "secure" indicates the latter property where the private inputs used for computation are kept secret from all other ...
Generating a supersingular elliptic curve such that nobody knows its endomorphism ring is a notoriously hard task, despite several isogeny-based protocols relying on such an object. A trusted setup is often proposed as a workaround, but several aspects rem ...
Many important problems in contemporary machine learning involve solving highly non- convex problems in sampling, optimization, or games. The absence of convexity poses significant challenges to convergence analysis of most training algorithms, and in some ...
We propose privacy-enhancing technologies for medical tests and personalized medicine methods, which utilize patients’ genomic data. Focusing specifically on a typical disease-susceptibility test, we develop a new architecture (between the patient and the ...
