37 citations · 159 across the 18 of their papers we have counts for
19 papers
Learning to Coordinate in Multi-Agent Systems: A Coordinated Actor-Critic Algorithm and Finite-Time Guarantees
Siliang Zeng, Tianyi Chen, Alfredo Garcia +1
Multi-agent reinforcement learning (MARL) has attracted much research attention recently. However, unlike its single-agent counterpart, many theoretical and algorithmic aspects of…
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…
Distributed Networked Learning with Correlated Data
Lingzhou Hong, Alfredo Garcia, Ceyhun Eksin
We consider a distributed estimation method in a setting with heterogeneous streams of correlated data distributed across nodes in a network. In the considered approach, linear mod…
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…
An Adaptive Online Ad Auction Scoring Algorithm for Revenue Maximization
Chenyang Li, Mingyi Hong, Randy Cogill +1
Sponsored search becomes an easy platform to match potential consumers' intent with merchants' advertising. Advertisers express their willingness to pay for each keyword in terms o…
Joint Access Point Selection and Power Allocation for Uplink Wireless Networks
Mingyi Hong, Alfredo Garcia, Jorge Barrera +1
We consider the distributed uplink resource allocation problem in a multi-carrier wireless network with multiple access points (APs). Each mobile user can optimize its own transmis…
Mechanism Design for Base Station Association and Resource Allocation in Downlink OFDMA Network
Mingyi Hong, Alfredo Garcia
We consider a resource management problem in a multi-cell downlink OFDMA network, whereby the goal is to find the optimal per base station resource allocation and user-base station…
Lower Bounds Optimization for Coordinated Linear Transmission Beamformer Design in Multicell Network Downlink
Mingyi Hong, Alfredo Garcia, J. Joaquin Escudero Garzas +1
We consider the coordinated downlink beamforming problem in a cellular network with the base stations (BSs) equipped with multiple antennas, and with each user equipped with a sing…
Joint Distributed Access Point Selection and Power Allocation in Cognitive Radio Networks
Mingyi Hong, Alfredo Garcia, Jorge Alviar
Spectrum management has been identified as a crucial step towards enabling the technology of the cognitive radio network (CRN). Most of the current works dealing with spectrum mana…
Distributed Uplink Resource Allocation in Cognitive Radio Networks -- Part II: Equilibria and Algorithms for Joint Access Point Selection and Power Allocation
Mingyi Hong, Alfredo Garcia, Jorge Barrera
In the first part of this paper, we have studied solely the spectrum sharing aspect of the above problem, and proposed algorithms for the CUs in the single AP network to efficientl…
Distributed Uplink Resource Allocation in Cognitive Radio Networks -- Part I: Equilibria and Algorithms for Power Allocation
Mingyi Hong, Alfredo Garcia, Stephen Wilson
Spectrum management has been identified as a crucial step towards enabling the technology of a cognitive radio network (CRN). Most of the current works dealing with spectrum manage…
Averaged Iterative Water-Filling Algorithm: Robustness and Convergence
Mingyi Hong, Alfredo Garcia
The convergence properties of the Iterative water-filling (IWF) based algorithms have been derived in the ideal situation where the transmitters in the network are able to obtain t…