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researcher

M. Carmosino

3 papers hereh-index 11724 citations32 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.LG2
  • quant-ph1

identity via Semantic Scholar / OpenAlex

most citedEfficient, Noise-Tolerant, and Private Learning via Boosting

4 citations · 4 across the 3 of their papers we have counts for

collaborators

3 papers

quant-ph2022

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…

cs.LG2022

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…

cs.LG2020★ 4 cited

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-…

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