b'Ali H. Sayed'

research

∙ 07/13/2023

Causal Influences over Social Learning Networks

This paper investigates causal influences between agents linked by a soc...

0 Mert Kayaalp, et al. ∙

research

∙ 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...

0 Ping Hu, et al. ∙

research

∙ 04/19/2023

Graph Exploration for Effective Multi-agent Q-Learning

This paper proposes an exploration technique for multi-agent reinforceme...

0 Ainur Zhaikhan, et al. ∙

research

∙ 04/07/2023

Compressed Regression over Adaptive Networks

In this work we derive the performance achievable by a network of distri...

0 Marco Carpentiero, et al. ∙

research

∙ 03/23/2023

Decentralized Adversarial Training over Graphs

The vulnerability of machine learning models to adversarial attacks has ...

0 Ying Cao, et al. ∙

research

∙ 03/10/2023

On the Fusion Strategies for Federated Decision Making

We consider the problem of information aggregation in federated decision...

0 Mert Kayaalp, et al. ∙

research

∙ 03/03/2023

Multi-Agent Adversarial Training Using Diffusion Learning

This work focuses on adversarial learning over graphs. We propose a gene...

0 Ying Cao, et al. ∙

research

∙ 02/08/2023

Policy Evaluation in Decentralized POMDPs with Belief Sharing

Most works on multi-agent reinforcement learning focus on scenarios wher...

0 Mert Kayaalp, et al. ∙

research

∙ 01/16/2023

Enforcing Privacy in Distributed Learning with Performance Guarantees

We study the privatization of distributed learning and optimization stra...

0 Elsa Rizk, et al. ∙

research

∙ 12/05/2022

Distributed Bayesian Learning of Dynamic States

This work studies networked agents cooperating to track a dynamical stat...

0 Mert Kayaalp, et al. ∙

research

∙ 11/23/2022

Discovering Influencers in Opinion Formation over Social Graphs

The adaptive social learning paradigm helps model how networked agents a...

0 Valentina Shumovskaia, et al. ∙

research

∙ 10/26/2022

Local Graph-homomorphic Processing for Privatized Distributed Systems

We study the generation of dependent random numbers in a distributed fas...

0 Elsa Rizk, et al. ∙

research

∙ 10/25/2022

Networked Signal and Information Processing

The article reviews significant advances in networked signal and informa...

0 Stefan Vlaski, et al. ∙

research

∙ 09/16/2022

Quantization for decentralized learning under subspace constraints

In this paper, we consider decentralized optimization problems where age...

8 Roula Nassif, et al. ∙

research

∙ 06/24/2022

A Fundamental Limit of Distributed Hypothesis Testing Under Memoryless Quantization

We study a distributed hypothesis testing setup where peripheral nodes s...

0 Yunus Inan, et al. ∙

research

∙ 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...

0 Mert Kayaalp, et al. ∙

research

∙ 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...

6 Roula Nassif, et al. ∙

research

∙ 03/14/2022

Privatized Graph Federated Learning

Federated learning is a semi-distributed algorithm, where a server commu...

18 Elsa Rizk, et al. ∙

research

∙ 03/14/2022

Optimal Aggregation Strategies for Social Learning over Graphs

Adaptive social learning is a useful tool for studying distributed decis...

0 Ping Hu, et al. ∙

research

∙ 03/11/2022

Online Graph Learning from Social Interactions

Social learning algorithms provide models for the formation of opinions ...

0 Valentina Shumovskaia, et al. ∙

research

∙ 03/04/2022

Random Information Sharing over Social Networks

This work studies the learning process over social networks under partia...

0 Mert Kayaalp, et al. ∙

research

∙ 01/26/2022

Social Learning under Randomized Collaborations

We study a social learning scheme where at every time instant, each agen...

0 Yunus Inan, et al. ∙

research

∙ 12/22/2021

Combinations of Adaptive Filters

Adaptive filters are at the core of many signal processing applications,...

6 Jerónimo Arenas-García, et al. ∙

research

∙ 12/17/2021

Learning from Heterogeneous Data Based on Social Interactions over Graphs

This work proposes a decentralized architecture, where individual agents...

20 Virginia Bordignon, et al. ∙

research

∙ 12/03/2021

Distributed Adaptive Learning Under Communication Constraints

This work examines adaptive distributed learning strategies designed to ...

8 Marco Carpentiero, et al. ∙

research

∙ 11/26/2021

Hidden Markov Modeling over Graphs

This work proposes a multi-agent filtering algorithm over graphs for fin...

0 Mert Kayaalp, et al. ∙

research

∙ 10/25/2021

Self-aware Social Learning over Graphs

In this paper we study the problem of social learning under multiple tru...

0 Konstantinos Ntemos, et al. ∙

research

∙ 04/26/2021

A Graph Federated Architecture with Privacy Preserving Learning

Federated learning involves a central processor that works with multiple...

0 Elsa Rizk, et al. ∙

research

∙ 03/29/2021

Competing Adaptive Networks

Adaptive networks have the capability to pursue solutions of global stoc...

0 Stefan Vlaski, et al. ∙

research

∙ 03/26/2021

Deception in Social Learning

A common assumption in the social learning literature is that agents exc...

0 Konstantinos Ntemos, et al. ∙

research

∙ 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 ...

14 Stefano Marano, et al. ∙

research

∙ 12/14/2020

Federated Learning under Importance Sampling

Federated learning encapsulates distributed learning strategies that are...

21 Elsa Rizk, et al. ∙

research

∙ 12/02/2020

Second-Order Guarantees in Federated Learning

Federated learning is a useful framework for centralized learning from d...

76 Stefan Vlaski, et al. ∙

research

∙ 10/26/2020

Optimal Importance Sampling for Federated Learning

Federated learning involves a mixture of centralized and decentralized p...

0 Elsa Rizk, et al. ∙

research

∙ 10/25/2020

Gramian-Based Adaptive Combination Policies for Diffusion Learning over Networks

This paper presents an adaptive combination strategy for distributed lea...

0 Y. Efe Erginbas, et al. ∙

research

∙ 10/23/2020

Network Classifiers Based on Social Learning

This work proposes a new way of combining independently trained classifi...

0 Virginia Bordignon, et al. ∙

research

∙ 10/23/2020

Graph-Homomorphic Perturbations for Private Decentralized Learning

Decentralized algorithms for stochastic optimization and learning rely o...

0 Stefan Vlaski, et al. ∙

research

∙ 10/06/2020

Dif-MAML: Decentralized Multi-Agent Meta-Learning

The objective of meta-learning is to exploit the knowledge obtained from...

0 Mert Kayaalp, et al. ∙

research

∙ 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...

0 Sulaiman A. Alghunaim, et al. ∙

research

∙ 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...

0 Lucas Cassano, et al. ∙

research

∙ 04/06/2020

Adaptive Social Learning

This work proposes a novel strategy for social learning by introducing t...

0 Virginia Bordignon, et al. ∙

research

∙ 04/04/2020

Tracking Performance of Online Stochastic Learners

The utilization of online stochastic algorithms is popular in large-scal...

0 Stefan Vlaski, et al. ∙

research

∙ 03/31/2020

Second-Order Guarantees in Centralized, Federated and Decentralized Nonconvex Optimization

Rapid advances in data collection and processing capabilities have allow...

0 Stefan Vlaski, et al. ∙

research

∙ 03/04/2020

Adaptation in Online Social Learning

This work studies social learning under non-stationary conditions. Altho...

0 Virginia Bordignon, et al. ∙

research

∙ 02/20/2020

Dynamic Federated Learning

Federated learning has emerged as an umbrella term for centralized coord...

0 Elsa Rizk, et al. ∙

research

∙ 02/12/2020

Learning Graph Influence from Social Interactions

In social learning, agents form their opinions or beliefs about certain ...

0 Vincenzo Matta, et al. ∙

research

∙ 01/07/2020

Multitask learning over graphs

The problem of learning simultaneously several related tasks has receive...

0 Roula Nassif, et al. ∙

research

∙ 12/18/2019

Inverse Graph Learning over Optimization Networks

Many inferential and learning tasks can be accomplished efficiently by m...

40 Vincenzo Matta, et al. ∙

research

∙ 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...

0 Vincenzo Matta, et al. ∙

research

∙ 10/30/2019

Social Learning with Partial Information Sharing

This work studies the learning abilities of agents sharing partial belie...

0 Virginia Bordignon, et al. ∙

Ali H. Sayed

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