
The Power of Random SymmetryBreaking in Nakamoto Consensus
Nakamoto consensus underlies the security of many of the world's largest...
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Achieving Statistical Optimality of Federated Learning: Beyond Stationary Points
Federated Learning (FL) is a promising framework that has great potentia...
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On Learning Overparameterized Neural Networks: A Functional Approximation Prospective
We consider training overparameterized twolayer neural networks with R...
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SpikeBased WinnerTakeAll Computation: Fundamental Limits and OrderOptimal Circuits
WinnerTakeAll (WTA) refers to the neural operation that selects a (typ...
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Distributed Learning with Adversarial Agents Under Relaxed Network Condition
This work studies the problem of nonBayesian learning over multiagent ...
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Collaboratively Learning the Best Option on Graphs, Using Bounded Local Memory
We consider multiarmed bandit problems in social groups wherein each in...
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Securing Distributed Machine Learning in High Dimensions
We consider securing a distributed machine learning system wherein the d...
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Collaboratively Learning the Best Option, Using Bounded Memory
We consider multiarmed bandit problems in social groups wherein each in...
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Distributed Statistical Machine Learning in Adversarial Settings: Byzantine Gradient Descent
We consider the problem of distributed statistical machine learning in a...
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Lili Su
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