
Dynamic Median Consensus Over Random Networks
This paper studies the problem of finding the median of N distinct numbe...
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On the Accuracy of Deterministic Models for Viral Spread on Networks
We consider the emergent behavior of viral spread when agents in a large...
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A hybrid variancereduced method for decentralized stochastic nonconvex optimization
This paper considers decentralized stochastic optimization over a networ...
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Meanfield Approximation for Stochastic Population Processes in Networks under Imperfect Information
This paper studies a general class of stochastic population processes in...
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Learning to Solve AC Optimal Power Flow by Differentiating through Holomorphic Embeddings
Alternating current optimal power flow (ACOPF) is one of the fundamenta...
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A fast randomized incremental gradient method for decentralized nonconvex optimization
We study decentralized nonconvex finitesum minimization problems descr...
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A nearoptimal stochastic gradient method for decentralized nonconvex finitesum optimization
This paper describes a nearoptimal stochastic firstorder gradient meth...
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PushSAGA: A decentralized stochastic algorithm with variance reduction over directed graphs
In this paper, we propose PushSAGA, a decentralized stochastic firstor...
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Distributed Gradient Flow: Nonsmoothness, Nonconvexity, and Saddle Point Evasion
The paper considers distributed gradient flow (DGF) for multiagent nonc...
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An improved convergence analysis for decentralized online stochastic nonconvex optimization
In this paper, we study decentralized online stochastic nonconvex optim...
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SADDOPT: Decentralized stochastic firstorder optimization over directed graphs
In this report, we study decentralized stochastic optimization to minimi...
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Gradient tracking and variance reduction for decentralized optimization and machine learning
Decentralized methods to solve finitesum minimization problems are impo...
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Resilient Distributed Recovery of Large Fields
This paper studies the resilient distributed recovery of large fields un...
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VarianceReduced Decentralized Stochastic Optimization with Gradient Tracking – Part II: GTSVRG
Decentralized stochastic optimization has recently benefited from gradie...
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Distributed Gradient Descent: Nonconvergence to Saddle Points and the StableManifold Theorem
The paper studies a distributed gradient descent (DGD) process and consi...
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Decentralized Stochastic FirstOrder Methods for Largescale Machine Learning
Decentralized consensusbased optimization is a general computational fr...
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Distributed Global Optimization by Annealing
The paper considers a distributed algorithm for global minimization of a...
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MATCHA: Speeding Up Decentralized SGD via Matching Decomposition Sampling
The tradeoff between convergence error and communication delays in dece...
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Distributed stochastic optimization with gradient tracking over stronglyconnected networks
In this paper, we study distributed stochastic optimization to minimize ...
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Annealing for Distributed Global Optimization
The paper proves convergence to global optima for a class of distributed...
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Clustering with Distributed Data
We consider Kmeans clustering in networked environments (e.g., internet...
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Coded Elastic Computing
Cloud providers have recently introduced lowpriority machines to reduce...
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Towards Gradient Free and Projection Free Stochastic Optimization
This paper focuses on the problem of constrainedstochastic optimization....
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Fully Distributed Cooperative Charging for Plugin Electric Vehicles in Constrained Power Networks
Plugin Electric Vehicles (PEVs) play a pivotal role in transportation e...
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The Internet of Things: Secure Distributed Inference
The growth in the number of devices connected to the Internet of Things ...
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Coded Iterative Computing using Substitute Decoding
In this paper, we propose a new coded computing technique called "substi...
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CIRFE: A Distributed Random Fields Estimator
This paper presents a communication efficient distributed algorithm, CIR...
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Localization in internets of mobile agents: A linear approach
Fifth generation (5G) networks providing much higher bandwidth and faste...
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Convergence Analysis of Belief Propagation on Gaussian Graphical Models
Gaussian belief propagation (GBP) is a recursive computation method that...
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Communication Optimality Tradeoffs For Distributed Estimation
This paper proposes Communication efficient REcursive Distributed estima...
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Distributed Convergence Verification for Gaussian Belief Propagation
Gaussian belief propagation (BP) is a computationally efficient method t...
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Topology Adaptive Graph Convolutional Networks
Convolution acts as a local feature extractor in convolutional neural ne...
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On the Exponential Rate of Convergence of Fictitious Play in Potential Games
The paper studies fictitious play (FP) learning dynamics in continuous t...
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On BestResponse Dynamics in Potential Games
The paper studies the convergence properties of (continuous) bestrespon...
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Fictitious Play in Potential Games
This work studies the convergence properties of continuoustime fictitio...
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Regular Potential Games
A fundamental problem with the Nash equilibrium concept is the existence...
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Convergence analysis of belief propagation for pairwise linear Gaussian models
Gaussian belief propagation (BP) has been widely used for distributed in...
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Structurally Observable Distributed Networks of Agents under Cost and Robustness Constraints
In many problems, agents cooperate locally so that a leader or fusion ce...
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Convergence Analysis of Distributed Inference with VectorValued Gaussian Belief Propagation
This paper considers inference over distributed linear Gaussian models u...
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QDLearning: A Collaborative Distributed Strategy for MultiAgent Reinforcement Learning Through Consensus + Innovations
The paper considers a class of multiagent Markov decision processes (MD...
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Soummya Kar
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Associate Professor Electrical and Computer Engineering at Carnegie Mellon University