( en | de | ru )

 

Disambiguation of "Giacomelli, Irene"

Author of the publication

copydeleteadd this publication to your clipboard
Additively Homomorphic UC Commitments with Optimal Amortized Overhead.

, , , , , and . Public Key Cryptography, volume 9020 of Lecture Notes in Computer Science, page 495-515. Springer, (2015)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Irene Drude

Entwicklung eines Twinribozyms zur spezifischen Reparatur einer Drei-Basendeletion innerhalb der onkogenen CTNNB1 mRNA. Uni Greifswald, (2009)

Irene Stumpf

Irene Eichelmann

Irene Tietz

Irene Müller

 

Other publications of authors with the same name

Model Extraction and Active Learning., , , , and . CoRR, (2018)Linear-Time Non-Malleable Codes in the Bit-Wise Independent Tampering Model., , , , and . ICITS, volume 10681 of Lecture Notes in Computer Science, page 1-25. Springer, (2017)Privacy-Preserving Ridge Regression with only Linearly-Homomorphic Encryption., , , , and . ACNS, volume 10892 of Lecture Notes in Computer Science, page 243-261. Springer, (2018)Monℤ2ka: Fast Maliciously Secure Two Party Computation on ℤ2k., , , and . IACR Cryptol. ePrint Arch., (2019)Privacy-Preserving Collaborative Prediction using Random Forests., , , , and . CoRR, (2018)Linear-Time Non-Malleable Codes in the Bit-Wise Independent Tampering Model., , , , and . IACR Cryptology ePrint Archive, (2016)Additively Homomorphic UC commitments with Optimal Amortized Overhead., , , , , and . IACR Cryptology ePrint Archive, (2014)Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting, , , and . (2017)cite arxiv:1709.01604.Additively Homomorphic UC Commitments with Optimal Amortized Overhead., , , , , and . Public Key Cryptography, volume 9020 of Lecture Notes in Computer Science, page 495-515. Springer, (2015)Overfitting, robustness, and malicious algorithms: A study of potential causes of privacy risk in machine learning., , , , and . J. Comput. Secur., 28 (1): 35-70 (2020)