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Found 12 papers, 2 papers with code
A Review of Cybersecurity Incidents in the Food and Agriculture Sector
The increasing utilization of emerging technologies in the Food & Agriculture (FA) sector has heightened the need for security to minimize cyber risks.
Towards Theoretical Understandings of Self-Consuming Generative Models
This paper tackles the emerging challenge of training generative models within a self-consuming loop, wherein successive generations of models are recursively trained on mixtures of real and synthetic data from previous generations.
Privacy-Preserving Distributed Learning for Residential Short-Term Load Forecasting
In the realm of power systems, the increasing involvement of residential users in load forecasting applications has heightened concerns about data privacy.
Enhancing Worker Recruitment in Collaborative Mobile Crowdsourcing: A Graph Neural Network Trust Evaluation Approach
The worker recruitment problem is modeled as an Undirected Complete Recruitment Graph (UCRG), for which a specific Tabu Search Recruitment (TSR) algorithm solution is proposed.
Bi-LRFusion: Bi-Directional LiDAR-Radar Fusion for 3D Dynamic Object Detection
LiDAR and Radar are two complementary sensing approaches in that LiDAR specializes in capturing an object's 3D shape while Radar provides longer detection ranges as well as velocity hints.
Error-based Knockoffs Inference for Controlled Feature Selection
Recently, the scheme of model-X knockoffs was proposed as a promising solution to address controlled feature selection under high-dimensional finite-sample settings.
Huber Additive Models for Non-stationary Time Series Analysis
Moreover, the error bound for non-stationary time series contains a discrepancy measure for the shifts of the data distributions over time.
Multi-Modal 3D Object Detection in Autonomous Driving: a Survey
In this survey, we first introduce the background of popular sensors used for self-driving, their data properties, and the corresponding object detection algorithms.
Impact of Local Energy Markets on the Distribution Systems: A Comprehensive Review
In recent years extensive research has been conducted on the development of different models that enable energy trading between prosumers and consumers due to expected high integration of distributed energy resources.
Multi-task Additive Models for Robust Estimation and Automatic Structure Discovery
For high-dimensional observations in real environment, e. g., Coronal Mass Ejections (CMEs) data, the learning performance of previous methods may be degraded seriously due to the complex non-Gaussian noise and the insufficiency of prior knowledge on variable structure.
Fast communication-efficient spectral clustering over distributed data
However, it is increasingly often that the data are located at a number of distributed sites, and one wishes to compute over all the data with low communication overhead.
K-nearest Neighbor Search by Random Projection Forests
Our theory can be used to refine the choice of random projections in the growth of trees, and experiments show that the effect is remarkable.
