Stefan Vlaski

ORCID

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 99

Top Venues

CoRR

ICASSP

IEEE Trans. Signal Process.

EUSIPCO

Publications

Roula Nassif, Soummya Kar, Stefan Vlaski
Learning Dynamics of Low-Precision Clipped SGD with Momentum. ICASSP (2024)
Roula Nassif, Stefan Vlaski, Marco Carpentiero, Vincenzo Matta, Ali H. Sayed
Differential error feedback for communication-efficient decentralized learning. CoRR (2024)
Dongyan Sui, Weichen Cao, Stefan Vlaski, Chun Guan, Siyang Leng
Non-Bayesian Social Learning with Multiview Observations. CoRR (2024)
Roula Nassif, Stefan Vlaski, Marco Carpentiero, Vincenzo Matta, Marc Antonini, Ali H. Sayed
Quantization for Decentralized Learning Under Subspace Constraints. IEEE Trans. Signal Process. 71 (2023)
Stefan Vlaski, Soummya Kar, Ali H. Sayed, José M. F. Moura
Networked Signal and Information Processing: Learning by multiagent systems. IEEE Signal Process. Mag. 40 (5) (2023)
Virginia Bordignon, Stefan Vlaski, Vincenzo Matta, Ali H. Sayed
Learning From Heterogeneous Data Based on Social Interactions Over Graphs. IEEE Trans. Inf. Theory 69 (5) (2023)
Elsa Rizk, Stefan Vlaski, Ali H. Sayed
Enforcing Privacy in Distributed Learning With Performance Guarantees. IEEE Trans. Signal Process. 71 (2023)
Ping Hu, Virginia Bordignon, Stefan Vlaski, Ali H. Sayed
Optimal Aggregation Strategies for Social Learning Over Graphs. IEEE Trans. Inf. Theory 69 (9) (2023)
Ying Cao, Elsa Rizk, Stefan Vlaski, Ali H. Sayed
Decentralized Adversarial Training over Graphs. CoRR (2023)
Elsa Rizk, Stefan Vlaski, Ali H. Sayed
Privatized graph federated learning. EURASIP J. Adv. Signal Process. 2023 (1) (2023)
Konstantinos Ntemos, Virginia Bordignon, Stefan Vlaski, Ali H. Sayed
Self-Aware Social Learning Over Graphs. IEEE Trans. Inf. Theory 69 (8) (2023)
Ying Cao, Elsa Rizk, Stefan Vlaski, Ali H. Sayed
Multi-Agent Adversarial Training Using Diffusion Learning. ICASSP (2023)
Christian A. Schroth, Stefan Vlaski, Abdelhak M. Zoubir
Robust M-Estimation Based Distributed Expectation Maximization Algorithm with Robust Aggregation. ICASSP (2023)
Ying Cao, Elsa Rizk, Stefan Vlaski, Ali H. Sayed
Multi-Agent Adversarial Training Using Diffusion Learning. CoRR (2023)
Christian A. Schroth, Stefan Vlaski, Abdelhak M. Zoubir
Attacks on Robust Distributed Learning Schemes via Sensitivity Curve Maximization. CoRR (2023)
Shreya Wadehra, Roula Nassif, Stefan Vlaski
Exact Subspace Diffusion for Decentralized Multitask Learning. CDC (2023)
Shreya Wadehra, Roula Nassif, Stefan Vlaski
Exact Subspace Diffusion for Decentralized Multitask Learning. CoRR (2023)
Chutian Wang, Stefan Vlaski
Robust Network Topologies for Distributed Learning. ICASSP (2023)
Elsa Rizk, Stefan Vlaski, Ali H. Sayed
Enforcing Privacy in Distributed Learning with Performance Guarantees. CoRR (2023)
Christian A. Schroth, Stefan Vlaski, Abdelhak M. Zoubir
Attacks on Robust Distributed Learning Schemes via Sensitivity Curve Maximization. DSP (2023)
Elsa Rizk, Stefan Vlaski, Ali H. Sayed
Local Graph-Homomorphic Processing for Privatized Distributed Systems. ICASSP (2023)
Konstantinos Ntemos, Virginia Bordignon, Stefan Vlaski, Ali H. Sayed
Social Learning with Disparate Hypotheses. EUSIPCO (2022)
Elsa Rizk, Stefan Vlaski, Ali H. Sayed
Local Graph-homomorphic Processing for Privatized Distributed Systems. CoRR (2022)
Valentina Shumovskaia, Konstantinos Ntemos, Stefan Vlaski, Ali H. Sayed
Online Graph Learning from Social Interactions. CoRR (2022)
Stefan Vlaski, Christian A. Schroth, Michael Muma, Abdelhak M. Zoubir
ROBUST AND EFFICIENT AGGREGATION FOR DISTRIBUTED LEARNING. EUSIPCO (2022)
Roula Nassif, Virginia Bordignon, Stefan Vlaski, Ali H. Sayed
Decentralized Learning in the Presence of Low-Rank Noise. ICASSP (2022)
Stefan Vlaski, Lieven Vandenberghe, Ali H. Sayed
Regularized Diffusion Adaptation via Conjugate Smoothing. IEEE Trans. Autom. Control. 67 (5) (2022)
Elsa Rizk, Stefan Vlaski, Ali H. Sayed
Federated Learning Under Importance Sampling. IEEE Trans. Signal Process. 70 (2022)
Mert Kayaalp, Virginia Bordignon, Stefan Vlaski, Vincenzo Matta, Ali H. Sayed
Distributed Bayesian Learning of Dynamic States. CoRR (2022)
Ping Hu, Virginia Bordignon, Stefan Vlaski, Ali H. Sayed
Optimal Aggregation Strategies for Social Learning over Graphs. CoRR (2022)
Elsa Rizk, Stefan Vlaski, Ali H. Sayed
Privatized Graph Federated Learning. CoRR (2022)
Roula Nassif, Stefan Vlaski, Marc Antonini, Marco Carpentiero, Vincenzo Matta, Ali H. Sayed
Finite Bit Quantization for Decentralized Learning Under Subspace Constraints. EUSIPCO (2022)
Stefan Vlaski, Ali H. Sayed
Second-Order Guarantees of Stochastic Gradient Descent in Nonconvex Optimization. IEEE Trans. Autom. Control. 67 (12) (2022)
Stefan Vlaski, Christian A. Schroth, Michael Muma, Abdelhak M. Zoubir
Robust and Efficient Aggregation for Distributed Learning. CoRR (2022)
Roula Nassif, Virginia Bordignon, Stefan Vlaski, Ali H. Sayed
Dencentralized learning in the presence of low-rank noise. CoRR (2022)
Valentina Shumovskaia, Konstantinos Ntemos, Stefan Vlaski, Ali H. Sayed
Explainability and Graph Learning From Social Interactions. IEEE Trans. Signal Inf. Process. over Networks 8 (2022)
Sofia Jegnell, Stefan Vlaski
Distributed Relatively Smooth Optimization. CDC (2022)
Stefan Vlaski, Soummya Kar, Ali H. Sayed, José M. F. Moura
Networked Signal and Information Processing. CoRR (2022)
Ping Hu, Virginia Bordignon, Stefan Vlaski, Ali H. Sayed
Optimal Combination Policies for Adaptive Social Learning. ICASSP (2022)
Roula Nassif, Stefan Vlaski, Marco Carpentiero, Vincenzo Matta, Marc Antonini, Ali H. Sayed
Quantization for decentralized learning under subspace constraints. CoRR (2022)
Mert Kayaalp, Stefan Vlaski, Ali H. Sayed
Distributed Meta-Learning with Networked Agents. EUSIPCO (2021)
Stefan Vlaski, Ali H. Sayed
Distributed Learning in Non-Convex Environments - Part I: Agreement at a Linear Rate. IEEE Trans. Signal Process. 69 (2021)
Virginia Bordignon, Stefan Vlaski, Vincenzo Matta, Ali H. Sayed
Network Classifiers Based on Social Learning. ICASSP (2021)
Elsa Rizk, Stefan Vlaski, Ali H. Sayed
Optimal Importance Sampling for Federated Learning. ICASSP (2021)
Konstantinos Ntemos, Virginia Bordignon, Stefan Vlaski, Ali H. Sayed
Self-aware Social Learning over Graphs. CoRR (2021)
Stefan Vlaski, Ali H. Sayed
Distributed Learning in Non-Convex Environments - Part II: Polynomial Escape From Saddle-Points. IEEE Trans. Signal Process. 69 (2021)
Konstantinos Ntemos, Virginia Bordignon, Stefan Vlaski, Ali H. Sayed
Social Learning Under Inferential Attacks. ICASSP (2021)
Valentina Shumovskaia, Konstantinos Ntemos, Stefan Vlaski, Ali H. Sayed
Online Graph Learning from Social Interactions. ACSCC (2021)
Stefan Vlaski, Ali H. Sayed
Competing Adaptive Networks. CoRR (2021)
Virginia Bordignon, Stefan Vlaski, Vincenzo Matta, Ali H. Sayed
Learning from Heterogeneous Data Based on Social Interactions over Graphs. CoRR (2021)
Stefan Vlaski, Ali H. Sayed
Graph-Homomorphic Perturbations for Private Decentralized Learning. ICASSP (2021)
Y. Efe Erginbas, Stefan Vlaski, Ali H. Sayed
Gramian-Based Adaptive Combination Policies for Diffusion Learning Over Networks. ICASSP (2021)
Konstantinos Ntemos, Virginia Bordignon, Stefan Vlaski, Ali H. Sayed
Deception in Social Learning. CoRR (2021)
Mert Kayaalp, Virginia Bordignon, Stefan Vlaski, Ali H. Sayed
Hidden Markov Modeling over Graphs. CoRR (2021)
Stefan Vlaski, Ali H. Sayed
Competing Adaptive Networks. SSP (2021)
Mert Kayaalp, Stefan Vlaski, Ali H. Sayed
Dif-MAML: Decentralized Multi-Agent Meta-Learning. CoRR (2020)
Roula Nassif, Stefan Vlaski, Ali H. Sayed
Adaptation and Learning Over Networks Under Subspace Constraints - Part II: Performance Analysis. IEEE Trans. Signal Process. 68 (2020)
Y. Efe Erginbas, Stefan Vlaski, Ali H. Sayed
Gramian-Based Adaptive Combination Policies for Diffusion Learning over Networks. CoRR (2020)
Elsa Rizk, Stefan Vlaski, Ali H. Sayed
Optimal Importance Sampling for Federated Learning. CoRR (2020)
Roula Nassif, Stefan Vlaski, Cédric Richard, Jie Chen, Ali H. Sayed
Multitask learning over graphs. CoRR (2020)
Stefan Vlaski, Elsa Rizk, Ali H. Sayed
Second-Order Guarantees in Federated Learning. ACSSC (2020)
Stefan Vlaski, Ali H. Sayed
Graph-Homomorphic Perturbations for Private Decentralized Learning. CoRR (2020)
Stefan Vlaski, Elsa Rizk, Ali H. Sayed
Tracking Performance of Online Stochastic Learners. IEEE Signal Process. Lett. 27 (2020)
Stefan Vlaski, Elsa Rizk, Ali H. Sayed
Second-Order Guarantees in Federated Learning. CoRR (2020)
Roula Nassif, Stefan Vlaski, Ali H. Sayed
Adaptation and Learning Over Networks Under Subspace Constraints - Part I: Stability Analysis. IEEE Trans. Signal Process. 68 (2020)
Stefan Vlaski, Ali H. Sayed
Second-Order Guarantees in Centralized, Federated and Decentralized Nonconvex Optimization. CoRR (2020)
Virginia Bordignon, Stefan Vlaski, Vincenzo Matta, Ali H. Sayed
Network Classifiers Based on Social Learning. CoRR (2020)
Elsa Rizk, Stefan Vlaski, Ali H. Sayed
Federated Learning under Importance Sampling. CoRR (2020)
Roula Nassif, Stefan Vlaski, Cédric Richard, Jie Chen, Ali H. Sayed
Multitask Learning Over Graphs: An Approach for Distributed, Streaming Machine Learning. IEEE Signal Process. Mag. 37 (3) (2020)
Stefan Vlaski, Elsa Rizk, Ali H. Sayed
Tracking Performance of Online Stochastic Learners. CoRR (2020)
Stefan Vlaski, Ali H. Sayed
Linear Speedup in Saddle-Point Escape for Decentralized Non-Convex Optimization. ICASSP (2020)
Konstantinos Ntemos, Virginia Bordignon, Stefan Vlaski, Ali H. Sayed
Social learning under inferential attacks. CoRR (2020)
Elsa Rizk, Stefan Vlaski, Ali H. Sayed
Dynamic Federated Learning. SPAWC (2020)
Elsa Rizk, Stefan Vlaski, Ali H. Sayed
Dynamic Federated Learning. CoRR (2020)
Stefan Vlaski, Ali H. Sayed
Second-order guarantees in centralized, federated and decentralized nonconvex optimization. Commun. Inf. Syst. 20 (3) (2020)
Bicheng Ying, Kun Yuan, Stefan Vlaski, Ali H. Sayed
Stochastic Learning Under Random Reshuffling With Constant Step-Sizes. IEEE Trans. Signal Process. 67 (2) (2019)
Roula Nassif, Stefan Vlaski, Ali H. Sayed
Adaptation and learning over networks under subspace constraints. CoRR (2019)
Stefan Vlaski, Ali H. Sayed
Distributed Learning in Non-Convex Environments - Part I: Agreement at a Linear Rate. CoRR (2019)
Stefan Vlaski, Ali H. Sayed
Distributed Learning in Non-Convex Environments - Part II: Polynomial Escape from Saddle-Points. CoRR (2019)
Stefan Vlaski, Ali H. Sayed
Linear Speedup in Saddle-Point Escape for Decentralized Non-Convex Optimization. CoRR (2019)
Roula Nassif, Stefan Vlaski, Ali H. Sayed
Distributed Learning over Networks under Subspace Constraints. ACSSC (2019)
Stefan Vlaski, Lieven Vandenberghe, Ali H. Sayed
Regularized Diffusion Adaptation via Conjugate Smoothing. CoRR (2019)
Ricardo Merched, Stefan Vlaski, Ali H. Sayed
Enhanced Diffusion Learning Over Networks. EUSIPCO (2019)
Roula Nassif, Stefan Vlaski, Ali H. Sayed
Distributed Inference over Networks under Subspace Constraints. ICASSP (2019)
Stefan Vlaski, Ali H. Sayed
Polynomial Escape-Time from Saddle Points in Distributed Non-Convex Optimization. CAMSAP (2019)
Stefan Vlaski, Ali H. Sayed
Diffusion Learning in Non-convex Environments. ICASSP (2019)
Stefan Vlaski, Ali H. Sayed
Second-Order Guarantees of Stochastic Gradient Descent in Non-Convex Optimization. CoRR (2019)
Roula Nassif, Stefan Vlaski, Ali H. Sayed
Adaptation and learning over networks under subspace constraints - Part II: Performance Analysis. CoRR (2019)
Roula Nassif, Stefan Vlaski, Cédric Richard, Ali H. Sayed
A Regularization Framework for Learning Over Multitask Graphs. IEEE Signal Process. Lett. 26 (2) (2019)
Roula Nassif, Stefan Vlaski, Ali H. Sayed
Learning over Multitask Graphs - Part II: Performance Analysis. CoRR (2018)
Roula Nassif, Stefan Vlaski, Ali H. Sayed
Learning over Multitask Graphs - Part I: Stability Analysis. CoRR (2018)
Bicheng Ying, Kun Yuan, Stefan Vlaski, Ali H. Sayed
Stochastic Learning under Random Reshuffling. CoRR (2018)
Stefan Vlaski, Hermina Petric Maretic, Roula Nassif, Pascal Frossard, Ali H. Sayed
Online Graph Learning from Sequential Data. DSW (2018)
Roula Nassif, Stefan Vlaski, Ali H. Sayed
Distributed Inference Over Multitask Graphs Under Smoothness. SPAWC (2018)
Bicheng Ying, Kun Yuan, Stefan Vlaski, Ali H. Sayed
On the performance of random reshuffling in stochastic learning. ITA (2017)
Sina Basir-Kazeruni, Stefan Vlaski, Hawraa Salami, Ali H. Sayed, Dejan Markovic
A blind Adaptive Stimulation Artifact Rejection (ASAR) engine for closed-loop implantable neuromodulation systems. NER (2017)
Kun Yuan, Bicheng Ying, Stefan Vlaski, Ali H. Sayed
Stochastic gradient descent with finite samples sizes. MLSP (2016)
Stefan Vlaski, Bicheng Ying, Ali H. Sayed
The brain strategy for online learning. GlobalSIP (2016)
Stefan Vlaski, Lieven Vandenberghe, Ali H. Sayed
Diffusion stochastic optimization with non-smooth regularizers. ICASSP (2016)
Stefan Vlaski, Ali H. Sayed
Proximal diffusion for stochastic costs with non-differentiable regularizers. ICASSP (2015)

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Publication Activity (10 Years)

Top Topics

Top Venues

Stefan Vlaski