Stefan Vlaski

Orcid: 0000-0002-0616-3076

According to our database1, Stefan Vlaski authored at least 71 papers between 2014 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
Privatized graph federated learning.
EURASIP J. Adv. Signal Process., December, 2023

Optimal Aggregation Strategies for Social Learning Over Graphs.
IEEE Trans. Inf. Theory, September, 2023

Self-Aware Social Learning Over Graphs.
IEEE Trans. Inf. Theory, August, 2023

Networked Signal and Information Processing: Learning by multiagent systems.
IEEE Signal Process. Mag., July, 2023

Learning From Heterogeneous Data Based on Social Interactions Over Graphs.
IEEE Trans. Inf. Theory, May, 2023

Enforcing Privacy in Distributed Learning With Performance Guarantees.
IEEE Trans. Signal Process., 2023

Quantization for Decentralized Learning Under Subspace Constraints.
IEEE Trans. Signal Process., 2023

Decentralized Adversarial Training over Graphs.
CoRR, 2023

Attacks on Robust Distributed Learning Schemes via Sensitivity Curve Maximization.
Proceedings of the 24th International Conference on Digital Signal Processing, 2023

Robust Network Topologies for Distributed Learning.
Proceedings of the IEEE International Conference on Acoustics, 2023

Robust M-Estimation Based Distributed Expectation Maximization Algorithm with Robust Aggregation.
Proceedings of the IEEE International Conference on Acoustics, 2023

Local Graph-Homomorphic Processing for Privatized Distributed Systems.
Proceedings of the IEEE International Conference on Acoustics, 2023

Multi-Agent Adversarial Training Using Diffusion Learning.
Proceedings of the IEEE International Conference on Acoustics, 2023

Exact Subspace Diffusion for Decentralized Multitask Learning.
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

2022
Federated Learning Under Importance Sampling.
IEEE Trans. Signal Process., 2022

Explainability and Graph Learning From Social Interactions.
IEEE Trans. Signal Inf. Process. over Networks, 2022

Regularized Diffusion Adaptation via Conjugate Smoothing.
IEEE Trans. Autom. Control., 2022

Second-Order Guarantees of Stochastic Gradient Descent in Nonconvex Optimization.
IEEE Trans. Autom. Control., 2022

Distributed Bayesian Learning of Dynamic States.
CoRR, 2022

Networked Signal and Information Processing.
CoRR, 2022

Dencentralized learning in the presence of low-rank noise.
CoRR, 2022

Decentralized Learning in the Presence of Low-Rank Noise.
Proceedings of the IEEE International Conference on Acoustics, 2022

Optimal Combination Policies for Adaptive Social Learning.
Proceedings of the IEEE International Conference on Acoustics, 2022

ROBUST AND EFFICIENT AGGREGATION FOR DISTRIBUTED LEARNING.
Proceedings of the 30th European Signal Processing Conference, 2022

Social Learning with Disparate Hypotheses.
Proceedings of the 30th European Signal Processing Conference, 2022

Finite Bit Quantization for Decentralized Learning Under Subspace Constraints.
Proceedings of the 30th European Signal Processing Conference, 2022

Distributed Relatively Smooth Optimization.
Proceedings of the 61st IEEE Conference on Decision and Control, 2022

2021
Distributed Learning in Non-Convex Environments - Part II: Polynomial Escape From Saddle-Points.
IEEE Trans. Signal Process., 2021

Distributed Learning in Non-Convex Environments - Part I: Agreement at a Linear Rate.
IEEE Trans. Signal Process., 2021

Hidden Markov Modeling over Graphs.
CoRR, 2021

Deception in Social Learning.
CoRR, 2021

Competing Adaptive Networks.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2021

Graph-Homomorphic Perturbations for Private Decentralized Learning.
Proceedings of the IEEE International Conference on Acoustics, 2021

Optimal Importance Sampling for Federated Learning.
Proceedings of the IEEE International Conference on Acoustics, 2021

Social Learning Under Inferential Attacks.
Proceedings of the IEEE International Conference on Acoustics, 2021

Gramian-Based Adaptive Combination Policies for Diffusion Learning Over Networks.
Proceedings of the IEEE International Conference on Acoustics, 2021

Network Classifiers Based on Social Learning.
Proceedings of the IEEE International Conference on Acoustics, 2021

Distributed Meta-Learning with Networked Agents.
Proceedings of the 29th European Signal Processing Conference, 2021

Online Graph Learning from Social Interactions.
Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021

2020
Adaptation and Learning Over Networks Under Subspace Constraints - Part II: Performance Analysis.
IEEE Trans. Signal Process., 2020

Adaptation and Learning Over Networks Under Subspace Constraints - Part I: Stability Analysis.
IEEE Trans. Signal Process., 2020

Multitask Learning Over Graphs: An Approach for Distributed, Streaming Machine Learning.
IEEE Signal Process. Mag., 2020

Tracking Performance of Online Stochastic Learners.
IEEE Signal Process. Lett., 2020

Dif-MAML: Decentralized Multi-Agent Meta-Learning.
CoRR, 2020

Multitask learning over graphs.
CoRR, 2020

Second-order guarantees in centralized, federated and decentralized nonconvex optimization.
Commun. Inf. Syst., 2020

Dynamic Federated Learning.
Proceedings of the 21st IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2020

Linear Speedup in Saddle-Point Escape for Decentralized Non-Convex Optimization.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Second-Order Guarantees in Federated Learning.
Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020

2019
Stochastic Learning Under Random Reshuffling With Constant Step-Sizes.
IEEE Trans. Signal Process., 2019

A Regularization Framework for Learning Over Multitask Graphs.
IEEE Signal Process. Lett., 2019

Second-Order Guarantees of Stochastic Gradient Descent in Non-Convex Optimization.
CoRR, 2019

Adaptation and learning over networks under subspace constraints.
CoRR, 2019

Diffusion Learning in Non-convex Environments.
Proceedings of the IEEE International Conference on Acoustics, 2019

Distributed Inference over Networks under Subspace Constraints.
Proceedings of the IEEE International Conference on Acoustics, 2019

Enhanced Diffusion Learning Over Networks.
Proceedings of the 27th European Signal Processing Conference, 2019

Polynomial Escape-Time from Saddle Points in Distributed Non-Convex Optimization.
Proceedings of the 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2019

Distributed Learning over Networks under Subspace Constraints.
Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

2018
Learning over Multitask Graphs - Part II: Performance Analysis.
CoRR, 2018

Learning over Multitask Graphs - Part I: Stability Analysis.
CoRR, 2018

Stochastic Learning under Random Reshuffling.
CoRR, 2018

Distributed Inference Over Multitask Graphs Under Smoothness.
Proceedings of the 19th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2018

Online Graph Learning from Sequential Data.
Proceedings of the 2018 IEEE Data Science Workshop, 2018

2017
A blind Adaptive Stimulation Artifact Rejection (ASAR) engine for closed-loop implantable neuromodulation systems.
Proceedings of the 8th International IEEE/EMBS Conference on Neural Engineering, 2017

On the performance of random reshuffling in stochastic learning.
Proceedings of the 2017 Information Theory and Applications Workshop, 2017

2016
Stochastic gradient descent with finite samples sizes.
Proceedings of the 26th IEEE International Workshop on Machine Learning for Signal Processing, 2016

Diffusion stochastic optimization with non-smooth regularizers.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

The brain strategy for online learning.
Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016

2015
Proximal diffusion for stochastic costs with non-differentiable regularizers.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

2014
Robust bootstrap based observation classification for Kalman Filtering in harsh LOS/NLOS environments.
Proceedings of the IEEE Workshop on Statistical Signal Processing, 2014

Robust bootstrap methods with an application to geolocation in harsh LOS/NLOS environments.
Proceedings of the IEEE International Conference on Acoustics, 2014


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