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Found 6 papers, 1 papers with code
A Selective Review on Statistical Methods for Massive Data Computation: Distributed Computing, Subsampling, and Minibatch Techniques
A huge amount of statistical methods for massive data computation have been rapidly developed in the past decades.
Quasi-Newton Updating for Large-Scale Distributed Learning
This considerably reduces the computation and communication complexity of the proposed method.
Network Gradient Descent Algorithm for Decentralized Federated Learning
The resulting NGD estimator can be statistically as efficient as the global estimator, if the learning rate is sufficiently small and the network structure is well balanced, even if the data are distributed heterogeneously.
Vehicle Re-identification Method Based on Vehicle Attribute and Mutual Exclusion Between Cameras
Vehicle Re-identification aims to identify a specific vehicle across time and camera view.
DC-Assisted Stabilization of Internal Oscillations for Improved Symbol Transitions in a Direct Antenna Modulation Transmitter
A detailed circuit model for a direct antenna modulation system is used to identify the origin of the oscillations and to justify the selection of the DC source.
Automatic, Dynamic, and Nearly Optimal Learning Rate Specification by Local Quadratic Approximation
In each update step, given the gradient direction, we locally approximate the loss function by a standard quadratic function of the learning rate.
