Publications de Mahsa Taziki | EPFL Graph Search

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The present invention concerns computer-implemented methods for training a machine learning model using Stochastic Gradient Descent, SGD. In one embodiment, the method is performed by a first computer in a distributed computing environment and comprises pe ...

The upsurge in the number of web users over the last two decades has resulted in a significant growth of online information. Recommenders are machine learning approach and are becoming one of the main ways to navigate the Internet. They recommend appropria ...

Asynchronous distributed machine learning solutions have proven very effective so far, but always assuming perfectly functioning workers. In practice, some of the workers can however exhibit Byzantine behavior, caused by hardware failures, software bugs, c ...

The upsurge in the number of web users over the last two decades has resulted in a significant growth of online information. This information growth calls for recommenders that personalize the in- formation proposed to each individual user. Nevertheless, p ...

The present invention concerns a method of determining an effect of a user action taken with respect to an item in a communication network. The item is associated with data content in the communication network. The method comprises: (a) determining (31) pu ...

Mahsa Taziki

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Byzantine machine learning

Privacy in Recommender Systems

Asynchronous Byzantine Machine Learning (the case of SGD)

D2P: Distance-Based Differential Privacy in Recommenders

Utility and privacy effects of a user action in a communication system

The Utility and Privacy Effects of a Click

Personalized and Private Peer-to-Peer Machine Learning