research
∙
04/24/2023
Model-Free Learning and Optimal Policy Design in Multi-Agent MDPs Under Probabilistic Agent Dropout
This work studies a multi-agent Markov decision process (MDP) that can u...
share
research
∙
12/22/2022
Nonlinear consensus+innovations under correlated heavy-tailed noises: Mean square convergence rate and asymptotics
We consider distributed recursive estimation of consensus+innovations ty...
research
∙
11/02/2022
Large deviations rates for stochastic gradient descent with strongly convex functions
Recent works have shown that high probability metrics with stochastic gr...
research
∙
10/28/2022
Secure Distributed Optimization Under Gradient Attacks
In this paper, we study secure distributed optimization against arbitrar...
research
∙
10/25/2022
Networked Signal and Information Processing
The article reviews significant advances in networked signal and informa...
research
∙
09/22/2022
One-Shot Federated Learning for Model Clustering and Learning in Heterogeneous Environments
We propose a communication efficient approach for federated learning in ...
research
∙
07/11/2022
Cluster-Based Control of Transition-Independent MDPs
This work studies the ability of a third-party influencer to control the...
research
∙
04/06/2022
Nonlinear gradient mappings and stochastic optimization: A general framework with applications to heavy-tail noise
We introduce a general framework for nonlinear stochastic gradient desce...
research
∙
02/07/2022
Variance reduced stochastic optimization over directed graphs with row and column stochastic weights
This paper proposes AB-SAGA, a first-order distributed stochastic optimi...
research
∙
02/01/2022
Gradient Based Clustering
We propose a general approach for distance based clustering, using the g...
research
∙
02/01/2022
Personalized Federated Learning via Convex Clustering
We propose a parametric family of algorithms for personalized federated ...
research
∙
12/18/2021
Distributed design of deterministic discrete-time privacy preserving average consensus for multi-agent systems through network augmentation
Average consensus protocols emerge with a central role in distributed sy...
research
∙
10/11/2021
Dynamic Median Consensus Over Random Networks
This paper studies the problem of finding the median of N distinct numbe...
research
∙
04/11/2021
On the Accuracy of Deterministic Models for Viral Spread on Networks
We consider the emergent behavior of viral spread when agents in a large...
research
∙
02/12/2021
A hybrid variance-reduced method for decentralized stochastic non-convex optimization
This paper considers decentralized stochastic optimization over a networ...
research
∙
01/24/2021
Mean-field Approximation for Stochastic Population Processes in Networks under Imperfect Information
This paper studies a general class of stochastic population processes in...
research
∙
12/16/2020
Learning to Solve AC Optimal Power Flow by Differentiating through Holomorphic Embeddings
Alternating current optimal power flow (AC-OPF) is one of the fundamenta...
research
∙
11/07/2020
A fast randomized incremental gradient method for decentralized non-convex optimization
We study decentralized non-convex finite-sum minimization problems descr...
research
∙
08/17/2020
A near-optimal stochastic gradient method for decentralized non-convex finite-sum optimization
This paper describes a near-optimal stochastic first-order gradient meth...
research
∙
08/13/2020
Push-SAGA: A decentralized stochastic algorithm with variance reduction over directed graphs
In this paper, we propose Push-SAGA, a decentralized stochastic first-or...
research
∙
08/12/2020
Distributed Gradient Flow: Nonsmoothness, Nonconvexity, and Saddle Point Evasion
The paper considers distributed gradient flow (DGF) for multi-agent nonc...
research
∙
08/10/2020
An improved convergence analysis for decentralized online stochastic non-convex optimization
In this paper, we study decentralized online stochastic non-convex optim...
research
∙
05/15/2020
S-ADDOPT: Decentralized stochastic first-order optimization over directed graphs
In this report, we study decentralized stochastic optimization to minimi...
research
∙
02/13/2020
Gradient tracking and variance reduction for decentralized optimization and machine learning
Decentralized methods to solve finite-sum minimization problems are impo...
research
∙
10/19/2019
Resilient Distributed Recovery of Large Fields
This paper studies the resilient distributed recovery of large fields un...
research
∙
10/08/2019
Variance-Reduced Decentralized Stochastic Optimization with Gradient Tracking – Part II: GT-SVRG
Decentralized stochastic optimization has recently benefited from gradie...
research
∙
08/07/2019
Distributed Gradient Descent: Nonconvergence to Saddle Points and the Stable-Manifold Theorem
The paper studies a distributed gradient descent (DGD) process and consi...
research
∙
07/23/2019
Decentralized Stochastic First-Order Methods for Large-scale Machine Learning
Decentralized consensus-based optimization is a general computational fr...
research
∙
07/20/2019
Distributed Global Optimization by Annealing
The paper considers a distributed algorithm for global minimization of a...
research
∙
05/23/2019
MATCHA: Speeding Up Decentralized SGD via Matching Decomposition Sampling
The trade-off between convergence error and communication delays in dece...
research
∙
03/18/2019
Distributed stochastic optimization with gradient tracking over strongly-connected networks
In this paper, we study distributed stochastic optimization to minimize ...
research
∙
03/18/2019
Annealing for Distributed Global Optimization
The paper proves convergence to global optima for a class of distributed...
research
∙
01/01/2019
Clustering with Distributed Data
We consider K-means clustering in networked environments (e.g., internet...
research
∙
12/16/2018
Coded Elastic Computing
Cloud providers have recently introduced low-priority machines to reduce...
research
∙
10/08/2018
Towards Gradient Free and Projection Free Stochastic Optimization
This paper focuses on the problem of constrainedstochastic optimization....
research
∙
06/28/2018
Fully Distributed Cooperative Charging for Plug-in Electric Vehicles in Constrained Power Networks
Plug-in Electric Vehicles (PEVs) play a pivotal role in transportation e...
research
∙
06/24/2018
The Internet of Things: Secure Distributed Inference
The growth in the number of devices connected to the Internet of Things ...
research
∙
05/15/2018
Coded Iterative Computing using Substitute Decoding
In this paper, we propose a new coded computing technique called "substi...
research
∙
02/14/2018
CIRFE: A Distributed Random Fields Estimator
This paper presents a communication efficient distributed algorithm, CIR...
research
∙
02/12/2018
Localization in internets of mobile agents: A linear approach
Fifth generation (5G) networks providing much higher bandwidth and faste...
research
∙
01/17/2018
Convergence Analysis of Belief Propagation on Gaussian Graphical Models
Gaussian belief propagation (GBP) is a recursive computation method that...
research
∙
01/12/2018
Communication Optimality Trade-offs For Distributed Estimation
This paper proposes Communication efficient REcursive Distributed estima...
research
∙
11/26/2017
Distributed Convergence Verification for Gaussian Belief Propagation
Gaussian belief propagation (BP) is a computationally efficient method t...
research
∙
10/28/2017
Topology Adaptive Graph Convolutional Networks
Convolution acts as a local feature extractor in convolutional neural ne...
research
∙
07/25/2017
On the Exponential Rate of Convergence of Fictitious Play in Potential Games
The paper studies fictitious play (FP) learning dynamics in continuous t...
research
∙
07/19/2017
On Best-Response Dynamics in Potential Games
The paper studies the convergence properties of (continuous) best-respon...
research
∙
07/19/2017
Fictitious Play in Potential Games
This work studies the convergence properties of continuous-time fictitio...
research
∙
07/19/2017
Regular Potential Games
A fundamental problem with the Nash equilibrium concept is the existence...
research
∙
06/12/2017
Convergence analysis of belief propagation for pairwise linear Gaussian models
Gaussian belief propagation (BP) has been widely used for distributed in...
research
∙
02/08/2017