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Found 4 papers, 1 papers with code
Empirical Bayes Estimation with Side Information: A Nonparametric Integrative Tweedie Approach
As the dimension of the auxiliary data increases, we accurately quantify the improvements in estimation risk and the associated deterioration in convergence rate.
FedLP: Layer-wise Pruning Mechanism for Communication-Computation Efficient Federated Learning
By adopting layer-wise pruning in local training and federated updating, we formulate an explicit FL pruning framework, FedLP (Federated Layer-wise Pruning), which is model-agnostic and universal for different types of deep learning models.
Learning-based Autonomous Channel Access in the Presence of Hidden Terminals
We consider the problem of autonomous channel access (AutoCA), where a group of terminals tries to discover a communication strategy with an access point (AP) via a common wireless channel in a distributed fashion.
No Spurious Local Minima in a Two Hidden Unit ReLU Network
Deep learning models can be efficiently optimized via stochastic gradient descent, but there is little theoretical evidence to support this.
