Παρακολούθηση
Stefan Vlaski
Stefan Vlaski
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα imperial.ac.uk - Αρχική σελίδα
Τίτλος
Παρατίθεται από
Παρατίθεται από
Έτος
Multitask learning over graphs: An approach for distributed, streaming machine learning
R Nassif, S Vlaski, C Richard, J Chen, AH Sayed
IEEE Signal Processing Magazine 37 (3), 14-25, 2020
512020
Distributed learning in non-convex environments—Part I: Agreement at a linear rate
S Vlaski, AH Sayed
IEEE Transactions on Signal Processing 69, 1242-1256, 2021
442021
Stochastic learning under random reshuffling with constant step-sizes
B Ying, K Yuan, S Vlaski, AH Sayed
IEEE Transactions on Signal Processing 67 (2), 474-489, 2018
38*2018
Distributed learning in non-convex environments—Part II: Polynomial escape from saddle-points
S Vlaski, AH Sayed
IEEE Transactions on Signal Processing 69, 1257-1270, 2021
372021
Stochastic gradient descent with finite samples sizes
K Yuan, B Ying, S Vlaski, AH Sayed
2016 IEEE 26th International Workshop on Machine Learning for Signal …, 2016
332016
Online graph learning from sequential data
S Vlaski, HP Maretić, R Nassif, P Frossard, AH Sayed
2018 IEEE Data Science Workshop (DSW), 190-194, 2018
242018
A blind Adaptive Stimulation Artifact Rejection (ASAR) engine for closed-loop implantable neuromodulation systems
S Basir-Kazeruni, S Vlaski, H Salami, AH Sayed, D Marković
2017 8th International IEEE/EMBS Conference on Neural Engineering (NER), 186-189, 2017
212017
Diffusion stochastic optimization with non-smooth regularizers
S Vlaski, L Vandenberghe, AH Sayed
2016 IEEE International Conference on Acoustics, Speech and Signal …, 2016
182016
Learning over multitask graphs—Part I: Stability analysis
R Nassif, S Vlaski, C Richard, AH Sayed
IEEE Open Journal of Signal Processing 1, 28-45, 2020
172020
Adaptation and Learning Over Networks Under Subspace Constraints—Part I: Stability Analysis
R Nassif, S Vlaski, AH Sayed
IEEE Transactions on Signal Processing 68, 1346-1360, 2020
172020
A regularization framework for learning over multitask graphs
R Nassif, S Vlaski, C Richard, AH Sayed
IEEE Signal Processing Letters 26 (2), 297-301, 2018
172018
Proximal diffusion for stochastic costs with non-differentiable regularizers
S Vlaski, AH Sayed
2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015
122015
Second-order guarantees of stochastic gradient descent in non-convex optimization
S Vlaski, AH Sayed
IEEE Transactions on Automatic Control, 2021
112021
Distributed inference over networks under subspace constraints
R Nassif, S Vlaski, AH Sayed
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019
112019
Learning over multitask graphs—Part II: Performance analysis
R Nassif, S Vlaski, C Richard, AH Sayed
IEEE Open Journal of Signal Processing 1, 46-63, 2020
102020
Diffusion learning in non-convex environments
S Vlaski, AH Sayed
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019
102019
Optimal importance sampling for federated learning
E Rizk, S Vlaski, AH Sayed
ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021
92021
Federated learning under importance sampling
E Rizk, S Vlaski, AH Sayed
arXiv preprint arXiv:2012.07383, 2020
92020
Adaptation and learning over networks under subspace constraints—Part II: Performance analysis
R Nassif, S Vlaski, AH Sayed
IEEE Transactions on Signal Processing 68, 2948-2962, 2020
92020
On the performance of random reshuffling in stochastic learning
B Ying, K Yuan, S Vlaski, AH Sayed
2017 Information Theory and Applications Workshop (ITA), 1-5, 2017
92017
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