8 citations · 27 across the 45 of their papers we have counts for
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cs.LG2024
Projected Forward Gradient-Guided Frank-Wolfe Algorithm via Variance Reduction
M. Rostami, S. S. Kia
This paper aims to enhance the use of the Frank-Wolfe (FW) algorithm for training deep neural networks. Similar to any gradient-based optimization algorithm, FW suffers from high c…
cs.LG2022
Federated Learning Using Variance Reduced Stochastic Gradient for Probabilistically Activated Agents
M. R. Rostami, S. S. Kia
This paper proposes an algorithm for Federated Learning (FL) with a two-layer structure that achieves both variance reduction and a faster convergence rate to an optimal solution i…
cs.LG2021
Concept Representation Learning with Contrastive Self-Supervised Learning
Daniel T. Chang
Concept-oriented deep learning (CODL) is a general approach to meet the future challenges for deep learning: (1) learning with little or no external supervision, (2) coping with te…