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Found 4 papers, 1 papers with code
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 absolute deviation (SCAD).
Robust Networked Federated Learning for Localization
This paper addresses the problem of localization, which is inherently non-convex and non-smooth in a federated setting where the data is distributed across a multitude of devices.
Moreau Envelope ADMM for Decentralized Weakly Convex Optimization
This paper proposes a proximal variant of the alternating direction method of multipliers (ADMM) for distributed optimization.
Structure Learning of Sparse GGMs over Multiple Access Networks
In Uncoded method, data symbols are scaled and transmitted through the channel.
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