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Found 6 papers, 0 papers with code
Nonnegative Matrix Factorization in Dimensionality Reduction: A Survey
Dimensionality Reduction plays a pivotal role in improving feature learning accuracy and reducing training time by eliminating redundant features, noise, and irrelevant data.
DE-CGAN: Boosting rTMS Treatment Prediction with Diversity Enhancing Conditional Generative Adversarial Networks
This work shows that increasing the diversity of a training dataset can improve classification model performance.
Graph-enabled Reinforcement Learning for Time Series Forecasting with Adaptive Intelligence
In this study, we propose a novel approach for predicting time-series data using GNN and monitoring with Reinforcement Learning (RL).
FedStack: Personalized activity monitoring using stacked federated learning
The federated learning architecture was applied to these models to build local and global models capable of state of the art performances.
A Preference Random Walk Algorithm for Link Prediction through Mutual Influence Nodes in Complex Networks
A comparison between the proposed method and other similarity-based methods (local, quasi-local, and global) has been performed, and results have been reported for 11 real-world networks.
Aspect-Based Opinion Extraction from Customer reviews
The proposed framework sequentially mines products aspects and users opinions, groups representative aspects by similarity, and generates an output summary.
