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Found 11 papers, 2 papers with code
Training Green AI Models Using Elite Samples
The substantial increase in AI model training has considerable environmental implications, mandating more energy-efficient and sustainable AI practices.
Transformer Multivariate Forecasting: Less is More?
From the model perspective, one of the PCA-enhanced models: PCA+Crossformer, reduces mean square errors (MSE) by 33. 3% and decreases runtime by 49. 2% on average.
Constraint Model for the Satellite Image Mosaic Selection Problem
More precisely, for this problem the input is an area of interest, several satellite images intersecting the area, a list of requirements relative to the image and the mosaic, such as cloud coverage percentage, image resolution, and a list of objectives to optimize.
Survey of Trustworthy AI: A Meta Decision of AI
When making strategic decisions, we are often confronted with overwhelming information to process.
The Emerging Artificial Intelligence Protocol for Hierarchical Information Network
The recent development of artificial intelligence enables a machine to achieve a human level of intelligence.
Strategic Decisions Survey, Taxonomy, and Future Directions from Artificial Intelligence Perspective
Strategic Decision-Making is always challenging because it is inherently uncertain, ambiguous, risky, and complex.
A Variant of Concurrent Constraint Programming on GPU
To solve this issue, we take a step back and contribute to a simple, intrinsically parallel, lock-free and formally correct programming language based on concurrent constraint programming.
A Data-Driven Reconstruction Technique based on Newton's Method for Emission Tomography
In this work, we present the Deep Newton Reconstruction Network (DNR-Net), a hybrid data-driven reconstruction technique for emission tomography inspired by Newton's method, a well-known iterative optimization algorithm.
A Bayesian Optimization Approach for Attenuation Correction in SPECT Brain Imaging
Photon attenuation and scatter are the two main physical factors affecting the diagnostic quality of SPECT in its applications in brain imaging.
Detecting Target-Area Link-Flooding DDoS Attacks using Traffic Analysis and Supervised Learning
A novel class of extreme link-flooding DDoS (Distributed Denial of Service) attacks is designed to cut off entire geographical areas such as cities and even countries from the Internet by simultaneously targeting a selected set of network links.
Challenges on Probabilistic Modeling for Evolving Networks
Due to the complexity of emerging networks, it is not always possible to build precise models in modeling and optimization (local and global) for networks.
