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Found 8 papers, 0 papers with code
From GARCH to Neural Network for Volatility Forecast
With the equivalence relationship established, we introduce an innovative approach, named GARCH-NN, for constructing NN-based volatility models.
Mitigating Communication Costs in Neural Networks: The Role of Dendritic Nonlinearity
Our comprehension of biological neuronal networks has profoundly influenced the evolution of artificial neural networks (ANNs).
Protective Self-Adaptive Pruning to Better Compress DNNs
Adaptive network pruning approach has recently drawn significant attention due to its excellent capability to identify the importance and redundancy of layers and filters and customize a suitable pruning solution.
NetMoST: A network-based machine learning approach for subtyping schizophrenia using polygenic SNP allele biomarkers
Subtyping neuropsychiatric disorders like schizophrenia is essential for improving the diagnosis and treatment of complex diseases.
A novel cluster internal evaluation index based on hyper-balls
It is crucial to evaluate the quality and determine the optimal number of clusters in cluster analysis.
Influential Recommender System
Traditional recommender systems are typically passive in that they try to adapt their recommendations to the user's historical interests.
NasHD: Efficient ViT Architecture Performance Ranking using Hyperdimensional Computing
Neural Architecture Search (NAS) is an automated architecture engineering method for deep learning design automation, which serves as an alternative to the manual and error-prone process of model development, selection, evaluation and performance estimation.
The SARAS Endoscopic Surgeon Action Detection (ESAD) dataset: Challenges and methods
For an autonomous robotic system, monitoring surgeon actions and assisting the main surgeon during a procedure can be very challenging.
