
A Graph Federated Architecture with Privacy Preserving Learning
Federated learning involves a central processor that works with multiple...
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Competing Adaptive Networks
Adaptive networks have the capability to pursue solutions of global stoc...
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Deception in Social Learning
A common assumption in the social learning literature is that agents exc...
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DecisionMaking Algorithms for Learning and Adaptation with Application to COVID19 Data
This work focuses on the development of a new family of decisionmaking ...
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Federated Learning under Importance Sampling
Federated learning encapsulates distributed learning strategies that are...
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SecondOrder Guarantees in Federated Learning
Federated learning is a useful framework for centralized learning from d...
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Optimal Importance Sampling for Federated Learning
Federated learning involves a mixture of centralized and decentralized p...
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GramianBased Adaptive Combination Policies for Diffusion Learning over Networks
This paper presents an adaptive combination strategy for distributed lea...
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Network Classifiers Based on Social Learning
This work proposes a new way of combining independently trained classifi...
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GraphHomomorphic Perturbations for Private Decentralized Learning
Decentralized algorithms for stochastic optimization and learning rely o...
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DifMAML: Decentralized MultiAgent MetaLearning
The objective of metalearning is to exploit the knowledge obtained from...
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A MultiAgent PrimalDual Strategy for Composite Optimization over Distributed Features
This work studies multiagent sharing optimization problems with the obj...
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Logical Team Qlearning: An approach towards factored policies in cooperative MARL
We address the challenge of learning factored policies in cooperative MA...
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Adaptive Social Learning
This work proposes a novel strategy for social learning by introducing t...
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Tracking Performance of Online Stochastic Learners
The utilization of online stochastic algorithms is popular in largescal...
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SecondOrder Guarantees in Centralized, Federated and Decentralized Nonconvex Optimization
Rapid advances in data collection and processing capabilities have allow...
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Adaptation in Online Social Learning
This work studies social learning under nonstationary conditions. Altho...
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Dynamic Federated Learning
Federated learning has emerged as an umbrella term for centralized coord...
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Learning Graph Influence from Social Interactions
In social learning, agents form their opinions or beliefs about certain ...
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Multitask learning over graphs
The problem of learning simultaneously several related tasks has receive...
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Inverse Graph Learning over Optimization Networks
Many inferential and learning tasks can be accomplished efficiently by m...
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Interplay between Topology and Social Learning over Weak Graphs
We consider a social learning problem, where a network of agents is inte...
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Social Learning with Partial Information Sharing
This work studies the learning abilities of agents sharing partial belie...
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Network Classifiers With Output Smoothing
This work introduces two strategies for training network classifiers wit...
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Linear Speedup in SaddlePoint Escape for Decentralized NonConvex Optimization
Under appropriate cooperation protocols and parameter choices, fully dec...
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Regularized Diffusion Adaptation via Conjugate Smoothing
The purpose of this work is to develop and study a distributed strategy ...
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ISL: Optimal Policy Learning With Optimal ExplorationExploitation TradeOff
Traditionally, offpolicy learning algorithms (such as Qlearning) and e...
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SecondOrder Guarantees of Stochastic Gradient Descent in NonConvex Optimization
Recent years have seen increased interest in performance guarantees of g...
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Distributed Learning in NonConvex Environments – Part II: Polynomial Escape from SaddlePoints
The diffusion strategy for distributed learning from streaming data empl...
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Distributed Learning in NonConvex Environments – Part I: Agreement at a Linear Rate
Driven by the need to solve increasingly complex optimization problems i...
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Topology Inference over Networks with Nonlinear Coupling
This work examines the problem of topology inference over discretetime ...
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Adaptation and learning over networks under subspace constraints – Part II: Performance Analysis
Part I of this paper considered optimization problems over networks wher...
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Adaptation and learning over networks under subspace constraints  Part I: Stability Analysis
This paper considers optimization problems over networks where agents ha...
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Adaptation and learning over networks under subspace constraints
This paper considers optimization problems over networks where agents ha...
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A Linearly Convergent Proximal Gradient Algorithm for Decentralized Optimization
Decentralized optimization is a promising paradigm that finds various ap...
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Learning ErdősRényi Graphs under Partial Observations: Concentration or Sparsity?
This work examines the problem of graph learning over a diffusion networ...
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On the Performance of Exact Diffusion over Adaptive Networks
Various biascorrection methods such as EXTRA, DIGing, and exact diffusi...
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Decentralized DecisionMaking Over MultiTask Networks
In important applications involving multitask networks with multiple ob...
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Dynamic Average Diffusion with randomized Coordinate Updates
This work derives and analyzes an online learning strategy for tracking ...
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MultiAgent Fully Decentralized Value Function Learning with Linear Convergence Rates
This work develops a fully decentralized multiagent algorithm for polic...
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MultiAgent Fully Decentralized OffPolicy Learning with Linear Convergence Rates
In this paper we develop a fully decentralized algorithm for policy eval...
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Learning Kolmogorov Models for Binary Random Variables
We summarize our recent findings, where we proposed a framework for lear...
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Learning Under Distributed Features
This work studies the problem of learning under both large data and larg...
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Local Tomography of Large Networks under the LowObservability Regime
This article studies the problem of reconstructing the topology of a net...
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Learning over Multitask Graphs  Part II: Performance Analysis
Part I of this paper formulated a multitask optimization problem where a...
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Learning over Multitask Graphs  Part I: Stability Analysis
This paper formulates a multitask optimization problem where agents in t...
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Walkman: A CommunicationEfficient RandomWalk Algorithm for Decentralized Optimization
This paper addresses consensus optimization problems in a multiagent ne...
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A CommunicationEfficient RandomWalk Algorithm for Decentralized Optimization
This paper addresses consensus optimization problem in a multiagent net...
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Stochastic Learning under Random Reshuffling
In empirical risk optimization, it has been observed that stochastic gra...
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Detection under OneBit Messaging over Adaptive Networks
This work studies the operation of multiagent networks engaged in binar...
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Ali H. Sayed
verfied profile
Dean of Engineering, EPFL, Switzerland