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04/27/2023
Attacks on Robust Distributed Learning Schemes via Sensitivity Curve Maximization
Distributed learning paradigms, such as federated or decentralized learn...
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04/14/2023
Exact Subspace Diffusion for Decentralized Multitask Learning
Classical paradigms for distributed learning, such as federated or decen...
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03/23/2023
Decentralized Adversarial Training over Graphs
The vulnerability of machine learning models to adversarial attacks has ...
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03/03/2023
Multi-Agent Adversarial Training Using Diffusion Learning
This work focuses on adversarial learning over graphs. We propose a gene...
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01/16/2023
Enforcing Privacy in Distributed Learning with Performance Guarantees
We study the privatization of distributed learning and optimization stra...
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12/05/2022
Distributed Bayesian Learning of Dynamic States
This work studies networked agents cooperating to track a dynamical stat...
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10/26/2022
Local Graph-homomorphic Processing for Privatized Distributed Systems
We study the generation of dependent random numbers in a distributed fas...
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10/25/2022
Networked Signal and Information Processing
The article reviews significant advances in networked signal and informa...
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09/16/2022
Quantization for decentralized learning under subspace constraints
In this paper, we consider decentralized optimization problems where age...
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04/01/2022
Robust and Efficient Aggregation for Distributed Learning
Distributed learning paradigms, such as federated and decentralized lear...
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03/18/2022
Dencentralized learning in the presence of low-rank noise
Observations collected by agents in a network may be unreliable due to o...
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03/14/2022
Privatized Graph Federated Learning
Federated learning is a semi-distributed algorithm, where a server commu...
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03/14/2022
Optimal Aggregation Strategies for Social Learning over Graphs
Adaptive social learning is a useful tool for studying distributed decis...
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03/11/2022
Online Graph Learning from Social Interactions
Social learning algorithms provide models for the formation of opinions ...
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12/17/2021
Learning from Heterogeneous Data Based on Social Interactions over Graphs
This work proposes a decentralized architecture, where individual agents...
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11/26/2021
Hidden Markov Modeling over Graphs
This work proposes a multi-agent filtering algorithm over graphs for fin...
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10/25/2021
Self-aware Social Learning over Graphs
In this paper we study the problem of social learning under multiple tru...
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03/29/2021
Competing Adaptive Networks
Adaptive networks have the capability to pursue solutions of global stoc...
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03/26/2021
Deception in Social Learning
A common assumption in the social learning literature is that agents exc...
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12/14/2020
Federated Learning under Importance Sampling
Federated learning encapsulates distributed learning strategies that are...
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12/02/2020
Second-Order Guarantees in Federated Learning
Federated learning is a useful framework for centralized learning from d...
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10/26/2020
Optimal Importance Sampling for Federated Learning
Federated learning involves a mixture of centralized and decentralized p...
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10/25/2020
Gramian-Based Adaptive Combination Policies for Diffusion Learning over Networks
This paper presents an adaptive combination strategy for distributed lea...
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10/23/2020
Network Classifiers Based on Social Learning
This work proposes a new way of combining independently trained classifi...
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10/23/2020
Graph-Homomorphic Perturbations for Private Decentralized Learning
Decentralized algorithms for stochastic optimization and learning rely o...
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10/06/2020
Dif-MAML: Decentralized Multi-Agent Meta-Learning
The objective of meta-learning is to exploit the knowledge obtained from...
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04/04/2020
Tracking Performance of Online Stochastic Learners
The utilization of online stochastic algorithms is popular in large-scal...
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03/31/2020
Second-Order Guarantees in Centralized, Federated and Decentralized Nonconvex Optimization
Rapid advances in data collection and processing capabilities have allow...
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02/20/2020
Dynamic Federated Learning
Federated learning has emerged as an umbrella term for centralized coord...
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01/07/2020
Multitask learning over graphs
The problem of learning simultaneously several related tasks has receive...
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10/30/2019
Linear Speedup in Saddle-Point Escape for Decentralized Non-Convex Optimization
Under appropriate cooperation protocols and parameter choices, fully dec...
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09/20/2019
Regularized Diffusion Adaptation via Conjugate Smoothing
The purpose of this work is to develop and study a distributed strategy ...
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08/19/2019
Second-Order Guarantees of Stochastic Gradient Descent in Non-Convex Optimization
Recent years have seen increased interest in performance guarantees of g...
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07/03/2019
Distributed Learning in Non-Convex Environments – Part II: Polynomial Escape from Saddle-Points
The diffusion strategy for distributed learning from streaming data empl...
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07/03/2019
Distributed Learning in Non-Convex Environments – Part I: Agreement at a Linear Rate
Driven by the need to solve increasingly complex optimization problems i...
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06/01/2019
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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05/21/2019
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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05/21/2019
Adaptation and learning over networks under subspace constraints
This paper considers optimization problems over networks where agents ha...
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05/22/2018
Learning over Multitask Graphs - Part II: Performance Analysis
Part I of this paper formulated a multitask optimization problem where a...
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05/22/2018
Learning over Multitask Graphs - Part I: Stability Analysis
This paper formulates a multitask optimization problem where agents in t...
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03/21/2018
