Communication Acceleration of Local Gradient Methods via an Accelerated Primal-Dual Algorithm with an Inexact Prox KAUST Learning to Attack Federated Learning: A Model-based Reinforcement Learning Attack Frame
They studied both the constrained fault-tolerant and the unconstrained fault-tolerant approaches generalized from employed greedy, FTFL, primal-dual, and linear optimization techniques. Both approaches allowed multiple client connection requests to be served, and for facilities to open for each site by...
Faster On-Device Training Using New Federated Momentum Algorithm FedDANE: A Federated Newton-Type Method Distributed Fixed Point Methods with Compressed Iterates Primal-dual methods for large-scale and distributed convex optimization and data analytics Parallel Restarted SPIDER - Communication Efficient Distr...
The integration of the primal–dual update mechanism not only enables efficient resource allocation and task scheduling within the constraints of limited resources, but also improves the scalability and efficiency of IoT networks. In addressing the challenge of optimizing resource allocation in IoT ...
Faster On-Device Training Using New Federated Momentum Algorithm FedDANE: A Federated Newton-Type Method Distributed Fixed Point Methods with Compressed Iterates Primal-dual methods for large-scale and distributed convex optimization and data analytics Parallel Restarted SPIDER - Communication Efficient Distr...
Communication Acceleration of Local Gradient Methods via an Accelerated Primal-Dual Algorithm with an Inexact Prox KAUST Learning to Attack Federated Learning: A Model-based Reinforcement Learning Attack Framework Tulane University code Coresets for Vertical Federated Learning: Regularized Linear Regression an...
Communication Acceleration of Local Gradient Methods via an Accelerated Primal-Dual Algorithm with an Inexact Prox KAUST Learning to Attack Federated Learning: A Model-based Reinforcement Learning Attack Framework Tulane University code Coresets for Vertical Federated Learning: Regularized Linear Regression an...
Communication Acceleration of Local Gradient Methods via an Accelerated Primal-Dual Algorithm with an Inexact Prox KAUST Learning to Attack Federated Learning: A Model-based Reinforcement Learning Attack Framework Tulane University code Coresets for Vertical Federated Learning: Regularized Linear Regression an...
Communication Acceleration of Local Gradient Methods via an Accelerated Primal-Dual Algorithm with an Inexact Prox KAUST Learning to Attack Federated Learning: A Model-based Reinforcement Learning Attack Framework Tulane University code Coresets for Vertical Federated Learning: Regularized Linear Regression an...
Communication Acceleration of Local Gradient Methods via an Accelerated Primal-Dual Algorithm with an Inexact Prox KAUST Learning to Attack Federated Learning: A Model-based Reinforcement Learning Attack Framework Tulane University code Coresets for Vertical Federated Learning: Regularized Linear Regression an...