37 citations · 159 across the 18 of their papers we have counts for
9 papers · 1 filter
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…
An Iterative Mechanism for Coupling Electricity Markets
Alfredo Garcia, Roohallah Khatami, Ceyhun Eksin +1
The coordinated operation of interconnected but locally controlled electricity markets is generally referred to as a "coupling". In this paper we propose a new mechanism design for…
Distributed Networked Real-time Learning
Alfredo Garcia, Luochao Wang, Jeff Huang +1
Many machine learning algorithms have been developed under the assumption that data sets are already available in batch form. Yet in many application domains data is only available…
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…
Swarming for Faster Convergence in Stochastic Optimization
Shi Pu, Alfredo Garcia
We study a distributed framework for stochastic optimization which is inspired by models of collective motion found in nature (e.g., swarming) with mild communication requirements.…
Zeroth Order Nonconvex Multi-Agent Optimization over Networks
Davood Hajinezhad, Mingyi Hong, Alfredo Garcia
In this paper, we consider distributed optimization problems over a multi-agent network, where each agent can only partially evaluate the objective function, and it is allowed to e…
A Flocking-based Approach for Distributed Stochastic Optimization
Shi Pu, Alfredo Garcia
In recent years, the paradigm of cloud computing has emerged as an architecture for computing that makes use of distributed (networked) computing resources. In this paper, we consi…
Iterative Mechanisms for Electricity Markets
Shi Pu, Alfredo Garcia
In order to deal with market power that sporadically results from contingencies (e.g., severe weather, plant outages) most electricity markets have institutions in charge of monito…