4 citations · 4 across the 1 of their papers we have counts for
3 papers
Decentralized Riemannian Gradient Descent on the Stiefel Manifold
Shixiang Chen, Alfredo Garcia, Mingyi Hong +1
We consider a distributed non-convex optimization where a network of agents aims at minimizing a global function over the Stiefel manifold. The global function is represented as a…
On the Local Linear Rate of Consensus on the Stiefel Manifold
Shixiang Chen, Alfredo Garcia, Mingyi Hong +1
We study the convergence properties of Riemannian gradient method for solving the consensus problem (for an undirected connected graph) over the Stiefel manifold. The Stiefel manif…
On Distributed Non-convex Optimization: Projected Subgradient Method For Weakly Convex Problems in Networks
Shixiang Chen, Alfredo Garcia, Shahin Shahrampour
The stochastic subgradient method is a widely-used algorithm for solving large-scale optimization problems arising in machine learning. Often these problems are neither smooth nor…