Concept
Information privacy law
Publications associées (98)
Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning
Distributed learning is the key for enabling training of modern large-scale machine learning models, through parallelising the learning process. Collaborative learning is essential for learning from privacy-sensitive data that is distributed across various ...
EPFL2024Arbitrary Decisions are a Hidden Cost of Differentially Private Training
Carmela González Troncoso, Bogdan Kulynych
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 Ga ...
New York2023Challenging the Assumptions: Rethinking Privacy, Bias, and Security in Machine Learning
Predictive models based on machine learning (ML) offer a compelling promise: bringing clarity and structure to complex natural and social environments. However, the use of ML poses substantial risks related to the privacy of their training data as well as ...
EPFL2023Sustainability and Ethicality are Peripheral to Students’ Software Design
Bryan Alexander Ford, Siara Ruth Isaac, Pierluca Borsò, Aditi Kothiyal
The conceptual design phase is a fascinating moment to observe how a design task is interpreted, as the (often implicit) relative importance students accord to the various requirements and constraints offers a window into the thinking underpinning their de ...
2023