4 citations · 5 across the 6 of their papers we have counts for
7 papers
On the Number of Quantifiers Needed to Define Boolean Functions
Marco Carmosino, Ronald Fagin, Neil Immerman +3
The number of quantifiers needed to express first-order (FO) properties is captured by two-player combinatorial games called multi-structural games. We analyze these games on binar…
Parallel Play Saves Quantifiers
Marco Carmosino, Ronald Fagin, Neil Immerman +4
The number of quantifiers needed to express first-order properties is captured by two-player combinatorial games called multi-structural (MS) games. We play these games on linear o…
Multi-Structural Games and Beyond
Marco Carmosino, Ronald Fagin, Neil Immerman +3
Multi-structural (MS) games are combinatorial games that capture the number of quantifiers of first-order sentences. On the face of their definition, MS games differ from Ehrenfeuc…
Creating quantum-resistant classical-classical OWFs from quantum-classical OWFs
Wei Zheng Teo, Marco Carmosino, Lior Horesh
One-way functions (OWF) are one of the most essential cryptographic primitives, the existence of which results in wide-ranging ramifications such as private-key encryption and prov…
Private Boosted Decision Trees via Smooth Re-Weighting
Vahid R. Asadi, Marco L. Carmosino, Mohammadmahdi Jahanara +2
Protecting the privacy of people whose data is used by machine learning algorithms is important. Differential Privacy is the appropriate mathematical framework for formal guarantee…
Learning with distributional inverters
Eric Binnendyk, Marco Carmosino, Antonina Kolokolova +2
We generalize the "indirect learning" technique of Furst et. al., 1991 to reduce from learning a concept class over a samplable distribution to learning the same concept class…
Efficient, Noise-Tolerant, and Private Learning via Boosting
Mark Bun, Marco Leandro Carmosino, Jessica Sorrell
We introduce a simple framework for designing private boosting algorithms. We give natural conditions under which these algorithms are differentially private, efficient, and noise-…