Carmela Troncoso
3 papers in the PaperMetrix corpus
Papers by this author
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Evading classifiers in discrete domains with provable optimality guarantees
2018 · arXiv (Cornell University)
Machine-learning models for security-critical applications such as bot, malware, or spam detection, operate in constrained discrete domains. These applications would benefit from having provable guarantees against adversarial examples. The existing literature on provable adversarial robustness …
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Arbitrary Decisions are a Hidden Cost of Differentially Private Training
2023
Mechanisms used in privacy-preserving machine learning often aim to guarantee differential privacy (DP) during model training. Practical DP-ensuring training methods use randomization when fitting model parameters to privacy-sensitive data (e.g., adding Gaussian noise to clipped …
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CookieGraph: Understanding and Detecting First-Party Tracking Cookies
2023
As third-party cookie blocking is becoming the norm in mainstream web browsers, advertisers and trackers have started to use first-party cookies for tracking. To understand this phenomenon, we conduct a differential measurement study with versus …