Publications by Mahsa Taziki | EPFL Graph Search

Byzantine machine learning

Rachid Guerraoui, Mahsa Taziki, El Mahdi El Mhamdi, Sébastien Louis Alexandre Rouault

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 ...

2020

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

Rachid Guerraoui, Mahsa Taziki

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 ...

2019

Asynchronous Byzantine Machine Learning (the case of SGD)

Rachid Guerraoui, Mahsa Taziki, El Mahdi El Mhamdi, Rhicheek Patra, Georgios Damaskinos

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 ...

2018

Privacy in Recommender Systems

Mahsa Taziki

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 ...

EPFL2018

Personalized and Private Peer-to-Peer Machine Learning

Rachid Guerraoui, Mahsa Taziki

2018

The Utility and Privacy Effects of a Click

Rachid Guerraoui, Anne-Marie Kermarrec, Mahsa Taziki

2017

D2P: Distance-Based Differential Privacy in Recommenders

Rachid Guerraoui, Anne-Marie Kermarrec, Mahsa Taziki, Rhicheek Patra

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 ...

Assoc Computing Machinery2015