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Decentralized projected Riemannian gradient method for smooth optimization on compact submanifolds
We consider the problem of decentralized nonconvex optimization over a compact
submanifold, where each local agent's objective function defined by the local dataset is …
submanifold, where each local agent's objective function defined by the local dataset is …
Decentralized matrix sensing: statistical guarantees and fast convergence
We explore the matrix sensing problem from near-isotropic linear measurements, distributed
across a network of agents modeled as an undirected graph, with no centralized node. We …
across a network of agents modeled as an undirected graph, with no centralized node. We …
Smoothing ADMM for Sparse-Penalized Quantile Regression With Non-Convex Penalties
This paper investigates quantile regression in the presence of non-convex and non-smooth
sparse penalties, such as the minimax concave penalty (MCP) and smoothly clipped …
sparse penalties, such as the minimax concave penalty (MCP) and smoothly clipped …
A Double Tracking Method for Optimization with Decentralized Generalized Orthogonality Constraints
In this paper, we consider the decentralized optimization problems with generalized
orthogonality constraints, where both the objective function and the constraint exhibit a …
orthogonality constraints, where both the objective function and the constraint exhibit a …