publications

A list of publications in journals and conference proceedings, by year of publication for published articles, and year of submission for preprints. A list of works is also available on Google Scholar.

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2026

  1. preprint
    Wan2026Decentralized.png
    Decentralized Multitask Learning over Learned Task Graphs
    Zirui Wan, and Stefan Vlaski
    available as arXiv:2608.26989, 2026
    arXiv
  2. TSIPN
    Peng2026Topology.png
    Topology-Independent Learning Error of the Weighted Mean under Label Poisoning Attacks in Heterogeneous Decentralized Learning
    Jie Peng, Weiyu Li, Stefan Vlaski, and Qing Ling
    IEEE Transactions on Signal and Information Processing over Networks, 2026
    arXiv HTML
  3. ICC
    Zhang2026Decentralized.png
    Decentralized AI Service Placement, Selection and Routing in Mobile Networks
    Jinkun Zhang, Stefan Vlaski, and Kin Leung
    In Proc. of 2026 IEEE International Conference on Communications, 2026
    arXiv HTML
  4. ICASSP
    Parameter Adaptation in Hidden Markov Models with Equal Exit Probabilities
    Haotian Pu, Dongyan Sui, Stefan Vlaski, and Siyang Leng
    In Proc. of 2026 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2026
    HTML
  5. ICASSP
    Wan2026Multitask.png
    Multitask Learning with Learned Task Relationships
    Zirui Wan, and Stefan Vlaski
    In Proc. of 2026 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2026
    arXiv HTML
  6. ICASSP
    Fainman2026Graph.png
    Graph-Aware Learning Rates for Decentralized Optimization
    Aaron Fainman, and Stefan Vlaski
    In Proc. of 2026 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2026
    arXiv HTML
  7. TSP
    Fainman2026Convergence.png
    On the Convergence of Decentralized Stochastic Gradient-Tracking with Finite-Time Consensus
    Aaron Fainman, and Stefan Vlaski
    IEEE Transactions on Signal Processing, 2026
    arXiv HTML
  8. TSP
    Zheng2026Quantitative.png
    Quantitative Error Feedback for Quantization Noise Reduction of Filtering over Graphs
    Xue Xian Zheng, Weihang Liu, Xin Lou, Stefan Vlaski, and Tareq Y Al-Naffouri
    IEEE Transactions on Signal Processing, 2026
    arXiv HTML

2025

  1. JMLR
    Peng2025Mean.png
    Mean Aggregator Is More Robust Than Robust Aggregators under Label Poisoning Attacks on Distributed Heterogeneous Data
    Jie Peng, Weiyu Li, Stefan Vlaski, and Qing Ling
    Journal of Machine Learning Research, 2025
    arXiv HTML
  2. Asilomar
    Pareto-Optimal Multi-Objective Learning over Graphs is Capable of Attaining Perfect Resource-Fairness: A Primal-Dual Min-Max Optimization Approach
    Sangwoo Park, Stefan Vlaski, and Lajos Hanzo
    In Proc. of 2025 59th Asilomar Conference on Signals, Systems, and Computers, 2025
    HTML
  3. EUSIPCO
    Park2025Scalable.png
    Scalable Min-Max Optimization via Primal-Dual Exact Pareto Optimization
    Sangwoo Park, Stefan Vlaski, and Lajos Hanzo
    In Proc. of 2025 33rd European Signal Processing Conference (EUSIPCO), 2025
    arXiv HTML
  4. EUSIPCO
    Sui2025Decentralized.png
    Decentralized Hidden Markov Modeling with Equal Exit Probabilities
    Dongyan Sui, Haitian Zheng, Siyang Leng, and Stefan Vlaski
    In Proc. of 2025 33rd European Signal Processing Conference (EUSIPCO), 2025
    arXiv HTML
  5. ICASSP
    Communication-Efficient Exact Diffusion for Decentralized Learning
    Gustavo Faia, Stefan Vlaski, and Roula Nassif
    In Proc. of 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2025
    HTML
  6. ICASSP
    Xiao2025Convergence.png
    Convergence Analysis of alpha-SVRG under Strong Convexity
    Sean Xiao, Sangwoo Park, and Stefan Vlaski
    In Proc. of 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2025
    arXiv HTML
  7. ICASSP
    Li2025Deep.png
    Deep-Relative-Trust-Based Diffusion for Decentralized Deep Learning
    Muyun Li, Aaron Fainman, and Stefan Vlaski
    In Proc. of 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2025
    arXiv HTML
  8. preprint
    Sui2025Alpha.png
    Alpha-Beta HMM: Hidden Markov Model Filtering with Equal Exit Probabilities and a Step-Size Parameter
    Dongyan Sui, Haotian Pu, Siyang Leng, and Stefan Vlaski
    available as arXiv:2504.01759, 2025
    arXiv
  9. TSP
    2406.18418.png
    Differential Error Feedback for Communication-Efficient Decentralized Learning
    Roula Nassif, Stefan Vlaski, Marco Carpentiero, Vincenzo Matta, and Ali H. Sayed
    IEEE Transactions on Signal Processing, 2025
    arXiv
  10. TIT
    CaoRizkVlaskiSayed22DecentralizedAdversarial.png
    Decentralized Adversarial Training over Graphs
    Ying Cao, Elsa Rizk, Stefan Vlaski, and Ali H. Sayed
    IEEE Transactions on Information Theory, 2025
    arXiv

2024

  1. preprint
    Schroth2024Sensitivity.png
    Sensitivity Curve Maximization: Attacking Robust Aggregators in Distributed Learning
    Christian A Schroth, Stefan Vlaski, and Abdelhak M Zoubir
    available as arXiv:2412.17740, 2024
    arXiv
  2. Asilomar
    Proximally Regularized Multitask Learning over Networks
    Stefan Vlaski, and Roula Nassif
    In Proc. of 2024 58th Asilomar Conference on Signals, Systems, and Computers, 2024
    HTML
  3. Asilomar
    Fainman2024Decentralized.png
    Decentralized Learning with Approximate Finite-Time Consensus
    Aaron Fainman, and Stefan Vlaski
    In Proc. of 2024 58th Asilomar Conference on Signals, Systems, and Computers, 2024
    arXiv HTML
  4. preprint
    Ran2024Towards.png
    Towards Scalable Semidefinite Programming: Optimal Metric ADMM with a Worst-Case Performance Guarantee
    Yifan Ran, Stefan Vlaski, and Wei Dai
    available as arXiv:2403.11533, 2024
    arXiv
  5. MLSP
    Decentralized Fusion of Experts Over Networks
    Marco Carpentiero, Vincenzo Matta, Stefan Vlaski, and Ali H. Sayed
    In Proc. of 2024 IEEE 34th International Workshop on Machine Learning for Signal Processing (MLSP), 2024
    DOI
  6. SPAWC
    Matching centralized learning performance via compressed decentralized learning with error feedback
    Roula Nassif, Marco Carpentiero, Stefan Vlaski, Vincenzo Matta, and Ali H. Sayed
    In Proc. of 2024 IEEE 25th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2024
    DOI
  7. Nonconvex Multitask Learning Over Networks
    Stefan Vlaski, and Roula Nassif
    In Proc. of 2024 32nd European Signal Processing Conference (EUSIPCO), 2024
    DOI
  8. CDC
    2407.20770.png
    Non-Bayesian Social Learning with Multiview Observations
    Dongyan Sui, Weichen Cao, Stefan Vlaski, Chun Guan, and Siyang Leng
    Proc. of 2024 63rd IEEE Conference on Decision and Control (CDC), Dec 2024
    arXiv
  9. SAM
    Differential Error Feedback for Communication-Efficient Decentralized Optimization
    Roula Nassif, Stefan Vlaski, Marco Carpentiero, Vincenzo Matta, and Ali H. Sayed
    In Proc. of 2024 IEEE 13rd Sensor Array and Multichannel Signal Processing Workshop (SAM), Dec 2024
    DOI
  10. ICASSP
    Learning Dynamics of Low-Precision Clipped SGD with Momentum
    Roula Nassif, Soummya Kar, and Stefan Vlaski
    In Proc. of 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Dec 2024
    DOI
  11. EUSIPCO
    10714953.png
    Learned Finite-Time Consensus for Distributed Optimization
    Aaron Fainman, and Stefan Vlaski
    In Proc. of 2024 32nd European Signal Processing Conference (EUSIPCO), Dec 2024
    DOI arXiv

2023

  1. CDC
    10384238.png
    Exact Subspace Diffusion for Decentralized Multitask Learning
    Shreya Wadehra, Roula Nassif, and Stefan Vlaski
    In Proc. of 2023 62nd IEEE Conference on Decision and Control (CDC), Dec 2023
    DOI arXiv
  2. TSP
    10261255.png
    Enforcing Privacy in Distributed Learning With Performance Guarantees
    Elsa Rizk, Stefan Vlaski, and Ali H. Sayed
    IEEE Transactions on Signal Processing, Dec 2023
    DOI arXiv
  3. EURASIP
    RizkVlaskiSayed22Privatized.png
    Privatized graph federated learning
    Elsa Rizk, Stefan Vlaski, and Ali H. Sayed
    EURASIP Journal on Advances in Signal Processing, Dec 2023
    DOI arXiv
  4. TSP
    10155165.png
    Quantization for Decentralized Learning Under Subspace Constraints
    Roula Nassif, Stefan Vlaski, Marco Carpentiero, Vincenzo Matta, Marc Antonini, and Ali H. Sayed
    IEEE Transactions on Signal Processing, Dec 2023
    DOI arXiv
  5. DSP
    10167919.png
    Attacks on Robust Distributed Learning Schemes via Sensitivity Curve Maximization
    Christian A. Schroth, Stefan Vlaski, and Abdelhak M. Zoubir
    In Proc. of 2023 24th International Conference on Digital Signal Processing (DSP), Dec 2023
    DOI arXiv
  6. ICASSP
    Robust Network Topologies for Distributed Learning
    Chutian Wang, and Stefan Vlaski
    In Proc. of 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Dec 2023
    DOI
  7. ICASSP
    Robust M-Estimation Based Distributed Expectation Maximization Algorithm with Robust Aggregation
    Christian A. Schroth, Stefan Vlaski, and Abdelhak M. Zoubir
    In Proc. of 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Dec 2023
    DOI
  8. ICASSP
    10095963.png
    Multi-Agent Adversarial Training Using Diffusion Learning
    Ying Cao, Elsa Rizk, Stefan Vlaski, and Ali H. Sayed
    In Proc. of 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Dec 2023
    DOI arXiv
  9. ICASSP
    10095990.png
    Local Graph-Homomorphic Processing for Privatized Distributed Systems
    Elsa Rizk, Stefan Vlaski, and Ali H. Sayed
    In Proc. of 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Dec 2023
    DOI arXiv
  10. TIT
    10138916.png
    Optimal Aggregation Strategies for Social Learning Over Graphs
    Ping Hu, Virginia Bordignon, Stefan Vlaski, and Ali H. Sayed
    IEEE Transactions on Information Theory, Dec 2023
    DOI arXiv
  11. TIT
    10124228.png
    Self-Aware Social Learning Over Graphs
    Konstantinos Ntemos, Virginia Bordignon, Stefan Vlaski, and Ali H. Sayed
    IEEE Transactions on Information Theory, Dec 2023
    DOI arXiv
  12. SPM
    VlaskiKarSayedMoura22Networked.png
    Networked Signal and Information Processing: Learning by Multiagent Systems
    Stefan Vlaski, Soummya Kar, Ali H. Sayed, and José M. F. Moura
    IEEE Signal Processing Magazine, Dec 2023
    DOI arXiv Website
  13. TIT
    BordignonVlaskiMattaSayed21Learning.png
    Learning from Heterogeneous Data Based on Social Interactions over Graphs
    Virginia Bordignon, Stefan Vlaski, Vincenzo Matta, and Ali H. Sayed
    IEEE Transactions on Information Theory, Dec 2023
    DOI arXiv Website

2022

  1. preprint
    KayaalpBordignonVlaskiSayed22DistributedBayesian.png
    Distributed Bayesian Learning of Dynamic States
    Mert Kayaalp, Virginia Bordignon, Stefan Vlaski, Vincenzo Matta, and Ali H. Sayed
    available as arXiv:2212.02565, Dec 2022
    arXiv
  2. TSPIN
    9956921.png
    Explainability and Graph Learning From Social Interactions
    Valentina Shumovskaia, Konstantinos Ntemos, Stefan Vlaski, and Ali H. Sayed
    IEEE Transactions on Signal and Information Processing over Networks, Dec 2022
    DOI arXiv
  3. TSP
    9904868.png
    Federated Learning Under Importance Sampling
    Elsa Rizk, Stefan Vlaski, and Ali H. Sayed
    IEEE Transactions on Signal Processing, Dec 2022
    DOI arXiv
  4. EUSIPCO
    9909947.png
    Social Learning with Disparate Hypotheses
    Konstantinos Ntemos, Virginia Bordignon, Stefan Vlaski, and Ali H. Sayed
    In Proc. of 2022 30th European Signal Processing Conference (EUSIPCO), Dec 2022
    DOI
  5. EUSIPCO
    NassifVlaskiAntoniniCarpentieroMattaSayed22Finite.png
    Finite Bit Quantization for Decentralized Learning Under Subspace Constraints
    Roula Nassif, Stefan Vlaski, Marc Antonini, Marco Carpentiero, Vincenzo Matta, and Ali H. Sayed
    In Proc. of 2022 30th European Signal Processing Conference (EUSIPCO), Dec 2022
    DOI
  6. EUSIPCO
    VlaskiSchrothMumaZoubir22Robust.png
    Robust and Efficient Aggregation for Distributed Learning
    Stefan Vlaski, Christian Schroth, Michael Muma, and Abdelhak M. Zoubir
    In Proc. of 2022 30th European Signal Processing Conference (EUSIPCO), Dec 2022
    DOI arXiv
  7. CDC
    JegnellVlaski22Distributed.png
    Distributed Relatively Smooth Optimization
    Sofia Jegnell, and Stefan Vlaski
    In Proc. IEEE Conference on Decision and Control (CDC), Dec 2022
    PDF Website
  8. ICASSP
    HuBordignonVlaskiSayed22OptimalConference.png
    Optimal Combination Policies for Adaptive Social Learning
    Ping Hu, Virginia Bordignon, Stefan Vlaski, and Ali H. Sayed
    In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Dec 2022
    DOI Website
  9. ICASSP
    NassifBordignonVlaskiSayed22Decentralized.png
    Decentralized Learning in the Presence of Low-Rank Noise
    Roula Nassif, Virginia Bordignon, Stefan Vlaski, and Ali H. Sayed
    In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Dec 2022
    DOI arXiv Website
  10. DSLW
    KayaalpBordignonVlaskiSayed22Hidden.png
    Hidden Markov Modeling Over Graphs
    Mert Kayaalp, Virginia Bordignon, Stefan Vlaski, and Ali H. Sayed
    In Proc. IEEE Data Science and Learning Workshop (DSLW), Dec 2022
    DOI arXiv Website
  11. OJSP
    KayaalpVlaskiSayed22Dif-MAML.png
    Dif-MAML: Decentralized Multi-Agent Meta-Learning
    Mert Kayaalp, Stefan Vlaski, and Ali H. Sayed
    IEEE Open Journal of Signal Processing, Dec 2022
    DOI arXiv Website

2021

  1. TAC
    VlaskiSayed21Second.png
    Second-Order Guarantees of Stochastic Gradient Descent in Non-Convex Optimization
    Stefan Vlaski, and Ali H. Sayed
    IEEE Transactions on Automatic Control, Dec 2021
    DOI arXiv Website
  2. EUSIPCO
    Distributed Meta-Learning with Networked Agents
    Mert Kayaalp, Stefan Vlaski, and Ali H. Sayed
    In Proc. European Signal Processing Conference (EUSIPCO), Dec 2021
    DOI
  3. SSP
    VlaskiSayed21Competing.png
    Competing Adaptive Networks
    Stefan Vlaski, and Ali H. Sayed
    In Proc. IEEE Statistical Signal Processing Workshop (SSP), Dec 2021
    DOI arXiv
  4. ICASSP
    ErginbasVlaskiSayed21Gramian.png
    Gramian-Based Adaptive Combination Policies for Diffusion Learning Over Networks
    Y. Efe Erginbas, Stefan Vlaski, and Ali H. Sayed
    In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Dec 2021
    DOI arXiv
  5. ICASSP
    NtemosBordignonVlaskiSayed22SocialLearning.png
    Social Learning Under Inferential Attacks
    Konstantinos Ntemos, Virginia Bordignon, Stefan Vlaski, and Ali H. Sayed
    In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Dec 2021
    DOI arXiv
  6. ICASSP
    BordignonVlaskiMattaSayed21Network.png
    Network Classifiers Based on Social Learning
    Virginia Bordignon, Stefan Vlaski, Vincenzo Matta, and Ali H. Sayed
    In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Dec 2021
    DOI arXiv
  7. ICASSP
    RizkVlaskiSayed21Optimal.png
    Optimal Importance Sampling for Federated Learning
    Elsa Rizk, Stefan Vlaski, and Ali H. Sayed
    In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Dec 2021
    DOI arXiv
  8. ICASSP
    VlaskiSayed21Graph-Homomorphic.png
    Graph-Homomorphic Perturbations for Private Decentralized Learning
    Stefan Vlaski, and Ali H. Sayed
    In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Dec 2021
    DOI arXiv
  9. TAC
    VlaskiVandenbergheSayed21Regularized.png
    Regularized Diffusion Adaptation via Conjugate Smoothing
    Stefan Vlaski, Lieven Vandenberghe, and Ali H. Sayed
    IEEE Transactions on Automatic Control, Dec 2021
    DOI arXiv
  10. patent
    Systems and methods for reducing noise caused by stimulation artifacts in neural signals received by neuro-modulation devices
    Dejan Marković, Ali H. Sayed, Sina Basir-Kazeruni, Stefan Vlaski, and Hawraa Salami
    US Patent US10980487B2, Dec 2021
  11. preprint
    NtemosBordignonVlaskiSayed21Deception.png
    Deception in Social Learning
    Konstantinos Ntemos, Virginia Bordignon, Stefan Vlaski, and Ali H. Sayed
    available as arXiv:2103.14729, Dec 2021
    arXiv
  12. TSP
    VlaskiSayed21DistributedPartII.png
    Distributed Learning in Non-Convex Environments — Part II: Polynomial Escape From Saddle-Points
    Stefan Vlaski, and Ali H. Sayed
    IEEE Transactions on Signal Processing, Dec 2021
    DOI arXiv Website
  13. TSP
    VlaskiSayed21DistributedPartI.png
    Distributed Learning in Non-Convex Environments — Part I: Agreement at a Linear Rate
    Stefan Vlaski, and Ali H. Sayed
    IEEE Transactions on Signal Processing, Dec 2021
    DOI arXiv Website
  14. Asilomar
    ShumovskaiaNtemosVlaskiSayed21Online.png
    Online Graph Learning from Social Interactions
    Valentina Shumovskaia, Konstantinos Ntemos, Stefan Vlaski, and Ali H. Sayed
    In Proc. Asilomar Conference on Signals, Systems, and Computers, Dec 2021
    DOI arXiv

2020

  1. Asilomar
    VlaskiRizkSayed20Second.png
    Second-Order Guarantees in Federated Learning
    Stefan Vlaski, Elsa Rizk, and Ali H. Sayed
    In Proc. Asilomar Conference on Signals, Systems, and Computers, Dec 2020
    DOI arXiv
  2. SPL
    VlaskiRizkSayed20Tracking.png
    Tracking Performance of Online Stochastic Learners
    Stefan Vlaski, Elsa Rizk, and Ali H. Sayed
    IEEE Signal Processing Letters, Dec 2020
    DOI arXiv
  3. SPAWC
    RizkVlaskiSayed20Dynamic.png
    Dynamic Federated Learning
    Elsa Rizk, Stefan Vlaski, and Ali H. Sayed
    In Proc. International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Dec 2020
    arXiv
  4. ICASSP
    VlaskiSayed20Linear.png
    Linear Speedup in Saddle-Point Escape for Decentralized Non-Convex Optimization
    Stefan Vlaski, and Ali H. Sayed
    In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Dec 2020
    DOI arXiv
  5. SPM
    NassifVlaskirichardChenSayed20Multitask.png
    Multitask Learning Over Graphs: An Approach for Distributed, Streaming Machine Learning
    Roula Nassif, Stefan Vlaski, Cédric Richard, Jie Chen, and Ali H. Sayed
    IEEE Signal Processing Magazine, Dec 2020
    DOI arXiv Website
  6. OJSP
    NassifVlaskiRichardSayed20LearningPartII.png
    Learning Over Multitask Graphs—Part II: Performance Analysis
    Roula Nassif, Stefan Vlaski, Cédric Richard, and Ali H. Sayed
    IEEE Open Journal of Signal Processing, Dec 2020
    DOI arXiv
  7. OJSP
    NassifVlaskiRichardSayed20LearningPartI.png
    Learning Over Multitask Graphs—Part I: Stability Analysis
    Roula Nassif, Stefan Vlaski, Cédric Richard, and Ali H. Sayed
    IEEE Open Journal of Signal Processing, Dec 2020
    DOI arXiv
  8. TSP
    NassifVlaskiSayed20AdaptationPartII.png
    Adaptation and Learning Over Networks Under Subspace Constraints—Part II: Performance Analysis
    Roula Nassif, Stefan Vlaski, and Ali H. Sayed
    IEEE Transactions on Signal Processing, Dec 2020
    DOI arXiv
  9. CIS
    VlaskiSayed20Second-OrderGuaranteesInCentralized.png
    Second-Order Guarantees in Centralized, Federated and Decentralized Nonconvex Optimization
    Stefan Vlaski, and Ali H. Sayed
    Communications in Information and Systems, Dec 2020
    arXiv
  10. patent
    Multi microphone wall detection and location estimation
    Mohamed Mansour, Srivatsan Kandadai, and Stefan Vlaski
    US Patent US10598543B1, Dec 2020
  11. TSP
    NassifVlaskiSayed20AdaptationPartI.png
    Adaptation and Learning Over Networks Under Subspace Constraints—Part I: Stability Analysis
    Roula Nassif, Stefan Vlaski, and Ali H. Sayed
    IEEE Transactions on Signal Processing, Dec 2020
    DOI arXiv

2019

  1. CAMSAP
    Polynomial Escape-Time from Saddle Points in Distributed Non-Convex Optimization
    Stefan Vlaski, and Ali H. Sayed
    In Proc. IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), Dec 2019
    DOI
  2. Asilomar
    Distributed Learning over Networks under Subspace Constraints
    Roula Nassif, Stefan Vlaski, and Ali H. Sayed
    In Proc. Asilomar Conference on Signals, Systems, and Computers, Dec 2019
    DOI
  3. EUSIPCO
    Enhanced Diffusion Learning Over Networks
    Ricardo Merched, Stefan Vlaski, and Ali H. Sayed
    In Proc. European Signal Processing Conference (EUSIPCO), Dec 2019
    DOI
  4. ICASSP
    Diffusion Learning in Non-convex Environments
    Stefan Vlaski, and Ali H. Sayed
    In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Dec 2019
    DOI
  5. ICASSP
    Distributed Inference over Networks under Subspace Constraints
    Roula Nassif, Stefan Vlaski, and Ali H. Sayed
    In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Dec 2019
    DOI
  6. SPL
    A Regularization Framework for Learning Over Multitask Graphs
    Roula Nassif, Stefan Vlaski, Cédric Richard, and Ali H. Sayed
    IEEE Signal Processing Letters, Dec 2019
    DOI
  7. TSP
    YingYuanVlaskiSayed19.png
    Stochastic Learning Under Random Reshuffling With Constant Step-Sizes
    Bicheng Ying, Kun Yuan, Stefan Vlaski, and Ali H. Sayed
    IEEE Transactions on Signal Processing, Dec 2019
    DOI arXiv

2018

  1. SPAWC
    Distributed Inference Over Multitask Graphs Under Smoothness
    Roula Nassif, Stefan Vlaski, and Ali H. Sayed
    In Proc. IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Dec 2018
    DOI
  2. DSW
    Online Graph Learning From Sequential Data
    Stefan Vlaski, Hermina P. Maretić, Roula Nassif, Pascal Frossard, and Ali H. Sayed
    In Proc. IEEE Data Science Workshop (DSW), Dec 2018
    DOI

2017

  1. NER
    A blind Adaptive Stimulation Artifact Rejection (ASAR) engine for closed-loop implantable neuromodulation systems
    Sina Basir-Kazeruni, Stefan Vlaski, Hawraa Salami, Ali H. Sayed, and Dejan Marković
    In Proc. International IEEE/EMBS Conference on Neural Engineering (NER), Dec 2017
    DOI
  2. ITA
    On the performance of random reshuffling in stochastic learning
    Bicheng Ying, Kun Yuan, Stefan Vlaski, and Ali H. Sayed
    In Proc. Information Theory and Applications Workshop (ITA), Dec 2017
    DOI

2016

  1. GlobalSIP
    The brain strategy for online learning
    Stefan Vlaski, Bicheng Ying, and Ali H. Sayed
    In Proc. IEEE Global Conference on Signal and Information Processing (GlobalSIP), Dec 2016
    DOI
  2. MLSP
    Stochastic gradient descent with finite samples sizes
    Kun Yuan, Bicheng Ying, Stefan Vlaski, and Ali H. Sayed
    In Proc. IEEE International Workshop on Machine Learning for Signal Processing (MLSP), Dec 2016
    DOI
  3. ICASSP
    Diffusion stochastic optimization with non-smooth regularizers
    Stefan Vlaski, Lieven Vandenberghe, and Ali H. Sayed
    In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Dec 2016
    DOI

2015

  1. ICASSP
    Proximal diffusion for stochastic costs with non-differentiable regularizers
    Stefan Vlaski, and Ali H. Sayed
    In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Dec 2015
    DOI

2014

  1. SSP
    Robust bootstrap based observation classification for Kalman Filtering in harsh LOS/NLOS environments
    Stefan Vlaski, and Abdelhak M. Zoubir
    In Proc. IEEE Workshop on Statistical Signal Processing (SSP), Dec 2014
    DOI
  2. ICASSP
    Robust bootstrap methods with an application to geolocation in harsh LOS/NLOS environments
    Stefan Vlaski, Michael Muma, and Abdelhak M. Zoubir
    In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Dec 2014
    DOI