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Maziar Sanjabi

44 papers hereh-index 2814.3k citations70 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author3
  • middle author36
  • last author4

Across the 43 of 44 papers where every author was matched, so the position is known.

fields
  • cs.LG17
  • cs.CV9
  • cs.CL8
  • math.OC6
  • cs.IR2
  • cs.AI1
Homepage
same name
  • Maziar Sanjabi — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20132025
most citedFederated Optimization in Heterogeneous Networks

436 citations · 1.4k across the 41 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.LG2019★ 8 cited

When Does Non-Orthogonal Tensor Decomposition Have No Spurious Local Minima?

Maziar Sanjabi, Sina Baharlouei, Meisam Razaviyayn +1

We study the optimization problem for decomposing d dimensional fourth-order Tensors with k non-orthogonal components. We derive \textit{deterministic} conditions under which s…

cs.LG2019★ 351 cited

Fair Resource Allocation in Federated Learning

Tian Li, Maziar Sanjabi, Ahmad Beirami +1

Federated learning involves training statistical models in massive, heterogeneous networks. Naively minimizing an aggregate loss function in such a network may disproportionately a…

cs.LG2019

Training generative networks using random discriminators

Babak Barazandeh, Meisam Razaviyayn, Maziar Sanjabi

In recent years, Generative Adversarial Networks (GANs) have drawn a lot of attentions for learning the underlying distribution of data in various applications. Despite their wide…

math.OC2019★ 138 cited

Solving a Class of Non-Convex Min-Max Games Using Iterative First Order Methods

Maher Nouiehed, Maziar Sanjabi, Tianjian Huang +2

Recent applications that arise in machine learning have surged significant interest in solving min-max saddle point games. This problem has been extensively studied in the convex-c…

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