PrivateLR: Differentially Private Regularized Logistic Regression. PrivateLR implements two differentially private algorithms for estimating L2-regularized logistic regression coefficients. A randomized algorithm F is epsilon-differentially private (C. Dwork, Differential Privacy, ICALP 2006), if |log(P(F(D) in S)) - log(P(F(D’) in S))| <= epsilon for any pair D, D’ of datasets that differ in exactly one element, any set S, and the randomness is taken over the choices F makes.

References in zbMATH (referenced in 27 articles , 1 standard article )

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  1. Derbeko, Philip; Dolev, Shlomi; Gudes, Ehud; Sharma, Shantanu: Security and privacy aspects in Mapreduce on clouds: A survey (2016)
  2. Kairouz, Peter; Oh, Sewoong; Viswanath, Pramod: Extremal mechanisms for local differential privacy (2016)
  3. Boreale, Michele; Pampaloni, Francesca: Quantitative information flow under generic leakage functions and adaptive adversaries (2015)
  4. Boreale, Michele; Paolini, Michela: Worst- and average-case privacy breaches in randomization mechanisms (2015)
  5. Brunel, Aloïs: Quantitative classical realizability (2015)
  6. Giurgiu, Andrei; Guerraoui, Rachid; Huguenin, Kévin; Kermarrec, Anne-Marie: Computing in social networks (2014)
  7. Hajian, Sara; Domingo-Ferrer, Josep; Farràs, Oriol: Generalization-based privacy preservation and discrimination prevention in data publishing and mining (2014)
  8. Kosinski, Michal; Bachrach, Yoram; Kohli, Pushmeet; Stillwell, David; Graepel, Thore: Manifestations of user personality in website choice and behaviour on online social networks (2014)
  9. Sarkar, Palash: On some connections between statistics and cryptology (2014)
  10. Chen, Rui; Fung, Benjamin C.M.; Mohammed, Noman; Desai, Bipin C.; Wang, Ke: Privacy-preserving trajectory data publishing by local suppression (2013)
  11. Domingo-Ferrer, Josep; Sánchez, David; Rufian-Torrell, Guillem: Anonymization of nominal data based on semantic marginality (2013)
  12. Dondi, Riccardo; Mauri, Giancarlo; Zoppis, Italo: The $l$-diversity problem: tractability and approximability (2013)
  13. Ji, Zhanglong; Elkan, Charles: Differential privacy based on importance weighting (2013)
  14. Kenthapadi, Krishnaram; Mishra, Nina; Nissim, Kobbi: Denials leak information: simulatable auditing (2013)
  15. Soria-Comas, Jordi; Domingo-Ferrer, Josep: Optimal data-independent noise for differential privacy (2013)
  16. Zhu, Tieying; Wang, Shanshan; Li, Xiangtao; Zhou, Zhiguo; Zhang, Riming: Structural attack to anonymous graph of social networks (2013)
  17. Berendt, Bettina: More than modelling and hiding: towards a comprehensive view of web mining and privacy (2012)
  18. Chakraborty, Supriyo; Charbiwala, Zainul; Choi, Haksoo; Raghavan, Kasturi Rangan; Srivastava, Mani B.: Balancing behavioral privacy and information utility in sensory data flows (2012)
  19. Comi, Marco; DasGupta, Bhaskar; Schapira, Michael; Srinivasan, Venkatakumar: On communication protocols that compute almost privately (2012)
  20. Liu, Jun-Qiang: Publishing set-valued data against realistic adversaries (2012)

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