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Decentralized Multitask Learning over Learned Task Graphs
Zirui Wan, Stefan Vlaski
This paper investigates decentralized multitask learning over networks when the underlying task relationships are unknown. While existing graph-regularized multitask frameworks typ…
Topology-Independent Robustness of the Weighted Mean under Label Poisoning Attacks in Heterogeneous Decentralized Learning
Jie Peng, Weiyu Li, Stefan Vlaski +1
Robustness to malicious attacks is crucial for practical decentralized signal processing and machine learning systems. A typical example of such attacks is label poisoning, meaning…
Multitask Learning with Learned Task Relationships
Zirui Wan, Stefan Vlaski
Classical consensus-based strategies for federated and decentralized learning are statistically suboptimal in the presence of heterogeneous local data or task distributions. As a r…
Convergence Analysis of alpha-SVRG under Strong Convexity
Sean Xiao, Sangwoo Park, Stefan Vlaski
Stochastic first-order methods for empirical risk minimization employ gradient approximations based on sampled data in lieu of exact gradients. Such constructions introduce noise i…