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STEFAN VLASKI
Author Info
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Name
Affiliation
Papers
STEFAN VLASKI
Dept. of Electr. Eng., Univ. of California Los Angeles, Los Angeles, CA, USA|c|
32
Collaborators
Citations
PageRank
25
23
11.39
Referers
Referees
References
41
295
259
Search Limit
100
295
Publications (32 rows)
Collaborators (25 rows)
Referers (41 rows)
Referees (100 rows)
Title
Citations
PageRank
Year
Regularized Diffusion Adaptation via Conjugate Smoothing
0
0.34
2022
Second-Order Guarantees of Stochastic Gradient Descent in Nonconvex Optimization
0
0.34
2022
OPTIMAL IMPORTANCE SAMPLING FOR FEDERATED LEARNING
0
0.34
2021
GRAMIAN-BASED ADAPTIVE COMBINATION POLICIES FOR DIFFUSION LEARNING OVER NETWORKS
0
0.34
2021
GRAPH-HOMOMORPHIC PERTURBATIONS FOR PRIVATE DECENTRALIZED LEARNING
0
0.34
2021
NETWORK CLASSIFIERS BASED ON SOCIAL LEARNING
0
0.34
2021
Distributed Meta-Learning with Networked Agents
0
0.34
2021
SOCIAL LEARNING UNDER INFERENTIAL ATTACKS
0
0.34
2021
COMPETING ADAPTIVE NETWORKS
0
0.34
2021
Second-Order Guarantees In Centralized, Federated And Decentralized Nonconvex Optimization
0
0.34
2020
Dynamic Federated Learning
0
0.34
2020
Tracking Performance Of Online Stochastic Learners
0
0.34
2020
Second-Order Guarantees in Federated Learning
0
0.34
2020
Multitask Learning Over Graphs: An Approach for Distributed, Streaming Machine Learning
5
0.40
2020
A Regularization Framework for Learning Over Multitask Graphs.
1
0.35
2019
Adaptation and learning over networks under subspace constraints.
0
0.34
2019
Adaptation and learning over networks under subspace constraints - Part II: Performance Analysis.
0
0.34
2019
Polynomial Escape-Time from Saddle Points in Distributed Non-Convex Optimization
0
0.34
2019
Stochastic Learning Under Random Reshuffling With Constant Step-Sizes.
1
0.36
2019
Distributed Inference Over Networks Under Subspace Constraints
1
0.35
2019
Enhanced Diffusion Learning Over Networks
0
0.34
2019
Distributed Learning over Networks under Subspace Constraints
0
0.34
2019
Diffusion Learning In Non-Convex Environments
0
0.34
2019
Stochastic Learning under Random Reshuffling.
3
0.44
2018
Learning over Multitask Graphs - Part II: Performance Analysis.
0
0.34
2018
Learning over Multitask Graphs - Part I: Stability Analysis.
1
0.35
2018
A blind Adaptive Stimulation Artifact Rejection (ASAR) engine for closed-loop implantable neuromodulation systems
0
0.34
2017
The Brain Strategy For Online Learning
0
0.34
2016
Stochastic gradient descent with finite samples sizes
2
0.38
2016
Diffusion stochastic optimization with non-smooth regularizers.
5
0.40
2016
Proximal Diffusion For Stochastic Costs With Non-Differentiable Regularizers
2
0.38
2015
Robust bootstrap methods with an application to geolocation in harsh LOS/NLOS environments
2
0.54
2014
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