Zobrazeno 1 - 10
of 167
pro vyhledávání: '"Shafi Goldwasser"'
Autor:
Jacob Andreas, Gašper Beguš, Michael M. Bronstein, Roee Diamant, Denley Delaney, Shane Gero, Shafi Goldwasser, David F. Gruber, Sarah de Haas, Peter Malkin, Nikolay Pavlov, Roger Payne, Giovanni Petri, Daniela Rus, Pratyusha Sharma, Dan Tchernov, Pernille Tønnesen, Antonio Torralba, Daniel Vogt, Robert J. Wood
Publikováno v:
iScience, Vol 25, Iss 6, Pp 104393- (2022)
Summary: Machine learning has been advancing dramatically over the past decade. Most strides are human-based applications due to the availability of large-scale datasets; however, opportunities are ripe to apply this technology to more deeply underst
Externí odkaz:
https://doaj.org/article/f34202408e454069a68e04a4fc029a68
Publikováno v:
2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bcc4ae93e223cc8fa030d2fd4500f6fd
https://doi.org/10.1109/focs54457.2022.00092
https://doi.org/10.1109/focs54457.2022.00092
Publikováno v:
Proc Natl Acad Sci U S A
Genome-wide association studies (GWASs) seek to identify genetic variants associated with a trait, and have been a powerful approach for understanding complex diseases. A critical challenge for GWASs has been the dependence on individual-level data t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d1c67590645d0e16a64a65304ddba866
https://doi.org/10.1073/pnas.1918257117
https://doi.org/10.1073/pnas.1918257117
Publikováno v:
SSRN Electronic Journal.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5a7306a325d233544216a6384d2cad75
https://doi.org/10.2139/ssrn.4074315
https://doi.org/10.2139/ssrn.4074315
Publikováno v:
Proceedings of the National Academy of Sciences of the United States of America
Significance We revisit the problem of ensuring statistically valid inferences across diverse target populations from a single source of training data. Our approach builds a surprising technical connection between the inference problem and a techniqu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b0752174a882fe3b69e55184c77aff7c
http://europepmc.org/articles/PMC8794832
http://europepmc.org/articles/PMC8794832
(Sender-)Deniable encryption provides a very strong privacy guarantee: a sender who is coerced by an attacker into "opening" their ciphertext after-the-fact is able to generate "fake" local random choices that are consistent with any plaintext of the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::214e77013629ce8ad3c7ae01b1d433d2
Publikováno v:
SSRN Electronic Journal.
Individuals expose personally identifying information to access a website or qualify for a loan, undermining privacy and security. Firms share proprietary information in dealmaking negotiations; if the deal fails, the negotiating partner may use that
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d6dfe8e6f7d2ea92588127e592f2789b
https://doi.org/10.2139/ssrn.3781082
https://doi.org/10.2139/ssrn.3781082
Publikováno v:
Advances in Cryptology – CRYPTO 2021 ISBN: 9783030842444
CRYPTO (2)
CRYPTO (2)
We define and construct Deniable Fully Homomorphic Encryption based on the Learning With Errors (LWE) polynomial hardness assumption. Deniable FHE enables storing encrypted data in the cloud to be processed securely without decryption, maintaining de
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::293591efc35129be3a76890b108b85e8
https://doi.org/10.1007/978-3-030-84245-1_22
https://doi.org/10.1007/978-3-030-84245-1_22
Publikováno v:
ITA
Often times, whether it be for adversarial or natural reasons, the distributions of test and training data differ. We give an algorithm that, given sets of training and test examples, identifies regions of test examples that cannot be predicted with
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9fc7c05f9eb6a1f61269611ec1110a71
https://doi.org/10.1109/ita50056.2020.9244996
https://doi.org/10.1109/ita50056.2020.9244996
Publikováno v:
Advances in Cryptology – EUROCRYPT 2020 ISBN: 9783030457235
EUROCRYPT (2)
EUROCRYPT (2)
The right of an individual to request the deletion of their personal data by an entity that might be storing it – referred to as the right to be forgotten – has been explicitly recognized, legislated, and exercised in several jurisdictions across
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7c6c66040aa33fbf7e17a8791ad48d3b
https://doi.org/10.1007/978-3-030-45724-2_13
https://doi.org/10.1007/978-3-030-45724-2_13