29 citations · 34 across the 4 of their papers we have counts for
4 papers
MixTailor: Mixed Gradient Aggregation for Robust Learning Against Tailored Attacks
Ali Ramezani-Kebrya, Iman Tabrizian, Fartash Faghri +1
Implementations of SGD on distributed systems create new vulnerabilities, which can be identified and misused by one or more adversarial agents. Recently, it has been shown that we…
Adaptive Gradient Quantization for Data-Parallel SGD
Fartash Faghri, Iman Tabrizian, Ilia Markov +3
Many communication-efficient variants of SGD use gradient quantization schemes. These schemes are often heuristic and fixed over the course of training. We empirically observe that…
Representation of Federated Learning via Worst-Case Robust Optimization Theory
Saeedeh Parsaeefard, Iman Tabrizian, Alberto Leon Garcia
Federated learning (FL) is a distributed learning approach where a set of end-user devices participate in the learning process by acting on their isolated local data sets. Here, we…
Artificial Intelligence as a Services (AI-aaS) on Software-Defined Infrastructure
Saeedeh Parsaeefard, Iman Tabrizian, Alberto Leon-Garcia
This paper investigates a paradigm for offering artificial intelligence as a service (AI-aaS) on software-defined infrastructures (SDIs). The increasing complexity of networking an…