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07/13/2023
Causal Influences over Social Learning Networks
This paper investigates causal influences between agents linked by a soc...
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06/15/2023
Non-Asymptotic Performance of Social Machine Learning Under Limited Data
This paper studies the probability of error associated with the social m...
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04/19/2023
Graph Exploration for Effective Multi-agent Q-Learning
This paper proposes an exploration technique for multi-agent reinforceme...
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04/07/2023
Compressed Regression over Adaptive Networks
In this work we derive the performance achievable by a network of distri...
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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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03/10/2023
On the Fusion Strategies for Federated Decision Making
We consider the problem of information aggregation in federated decision...
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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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02/08/2023
Policy Evaluation in Decentralized POMDPs with Belief Sharing
Most works on multi-agent reinforcement learning focus on scenarios wher...
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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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11/23/2022
Discovering Influencers in Opinion Formation over Social Graphs
The adaptive social learning paradigm helps model how networked agents a...
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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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06/24/2022
A Fundamental Limit of Distributed Hypothesis Testing Under Memoryless Quantization
We study a distributed hypothesis testing setup where peripheral nodes s...
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04/28/2022
On the Arithmetic and Geometric Fusion of Beliefs for Distributed Inference
We study the asymptotic learning rates under linear and log-linear combi...
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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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03/04/2022
Random Information Sharing over Social Networks
This work studies the learning process over social networks under partia...
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01/26/2022
Social Learning under Randomized Collaborations
We study a social learning scheme where at every time instant, each agen...
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12/22/2021
Combinations of Adaptive Filters
Adaptive filters are at the core of many signal processing applications,...
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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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12/03/2021
Distributed Adaptive Learning Under Communication Constraints
This work examines adaptive distributed learning strategies designed to ...
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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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04/26/2021
A Graph Federated Architecture with Privacy Preserving Learning
Federated learning involves a central processor that works with multiple...
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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
Decision-Making Algorithms for Learning and Adaptation with Application to COVID-19 Data
This work focuses on the development of a new family of decision-making ...
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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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06/15/2020
A Multi-Agent Primal-Dual Strategy for Composite Optimization over Distributed Features
This work studies multi-agent sharing optimization problems with the obj...
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06/05/2020
Logical Team Q-learning: An approach towards factored policies in cooperative MARL
We address the challenge of learning factored policies in cooperative MA...
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04/06/2020
Adaptive Social Learning
This work proposes a novel strategy for social learning by introducing t...
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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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03/04/2020
Adaptation in Online Social Learning
This work studies social learning under non-stationary conditions. Altho...
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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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02/12/2020
Learning Graph Influence from Social Interactions
In social learning, agents form their opinions or beliefs about certain ...
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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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12/18/2019
Inverse Graph Learning over Optimization Networks
Many inferential and learning tasks can be accomplished efficiently by m...
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10/30/2019
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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10/30/2019