2 citations · 5 across the 4 of their papers we have counts for
4 papers
Achieving Linear Speedup in Non-IID Federated Bilevel Learning
Minhui Huang, Dewei Zhang, Kaiyi Ji
Federated bilevel optimization has received increasing attention in various emerging machine learning and communication applications. Recently, several Hessian-vector-based algorit…
Riemannian Stochastic Gradient Method for Nested Composition Optimization
Dewei Zhang, Sam Davanloo Tajbakhsh
This work considers optimization of composition of functions in a nested form over Riemannian manifolds where each function contains an expectation. This type of problems is gainin…
Riemannian Stochastic Variance-Reduced Cubic Regularized Newton Method for Submanifold Optimization
Dewei Zhang, Sam Davanloo Tajbakhsh
We propose a stochastic variance-reduced cubic regularized Newton algorithm to optimize the finite-sum problem over a Riemannian submanifold of the Euclidean space. The proposed al…
A first-order optimization algorithm for statistical learning with hierarchical sparsity structure
Dewei Zhang, Yin Liu, Sam Davanloo Tajbakhsh
In many statistical learning problems, it is desired that the optimal solution conforms to an a priori known sparsity structure represented by a directed acyclic graph. Inducing su…