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Found 10 papers, 0 papers with code
FedLED: Label-Free Equipment Fault Diagnosis with Vertical Federated Transfer Learning
Intelligent equipment fault diagnosis based on Federated Transfer Learning (FTL) attracts considerable attention from both academia and industry.
Adaptive hedging horizon and hedging performance estimation
The EMD hedging method family exhibits superior performance on the VaR criterion compared with the minimum variance hedging method.
A PubMedBERT-based Classifier with Data Augmentation Strategy for Detecting Medication Mentions in Tweets
As a major social media platform, Twitter publishes a large number of user-generated text (tweets) on a daily basis.
Backstepping Mean-Field Density Control for Large-Scale Heterogeneous Nonlinear Stochastic Systems
In this work, we present a backstepping design algorithm that extends density control to heterogeneous and higher-order stochastic systems in strict-feedback forms.
Distributed Mean-Field Density Estimation for Large-Scale Systems
This work studies how to estimate the mean-field density of large-scale systems in a distributed manner.
Feedback Interconnected Mean-Field Density Estimation and Control
Specifically, we propose new density control laws which use the mean-field density and its gradient as feedback, and prove that they are globally input-to-state stable (ISS) with respect to estimation errors.
Latent Dirichlet Allocation Model Training with Differential Privacy
To address the privacy issue in LDA, we systematically investigate the privacy protection of the main-stream LDA training algorithm based on Collapsed Gibbs Sampling (CGS) and propose several differentially private LDA algorithms for typical training scenarios.
Transporting Robotic Swarms via Mean-Field Feedback Control
With the rapid development of AI and robotics, transporting a large swarm of networked robots has foreseeable applications in the near future.
OL4EL: Online Learning for Edge-cloud Collaborative Learning on Heterogeneous Edges with Resource Constraints
However, heterogeneous and limited computation and communication resources on edge servers (or edges) pose great challenges on distributed ML and formulate a new paradigm of Edge Learning (i. e. edge-cloud collaborative machine learning).
Leak Event Identification in Water Systems Using High Order CRF
Today, detection of anomalous events in civil infrastructures (e. g. water pipe breaks and leaks) is time consuming and often takes hours or days.
