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Tech Xplore22h
Bilinear sequence regression model shows why AI excels at learning from word sequences
Researchers at EPFL have created a mathematical model that helps explain how breaking language into sequences makes modern AI ...
IEEE1mon
Combining Fuzzy Vector Quantization With Linear Discriminant Analysis for Continuous Human Movement Recognition
Abstract: In this paper, a novel method for continuous human movement recognition based on fuzzy vector quantization (FVQ) and linear discriminant analysis ... The proposed algorithm combines FVQ and ...
The Fabricator2mon
Linear versus sketched patterns for real-time demonstration
It was easy to locate the holes where the bolts were (see Figure 3). My sage advice from all this is that linear vector-driven patterns are useful for quick modeling but are not as versatile or as ...
Frontiers6mon
EEG channel and feature investigation in binary and multiple motor imagery task predictions
They used the Filter Bank Common Spatial Pattern (FBCSP) algorithm by providing multi-resolution frequency decomposition and linear classification algorithms ... and Learning Vector Quantization ...
Scientific Research Publishing10mon
Martín-Valdivia, M.T., Ureña-López, L.A. and García-Vega, M. (2007) The Learning Vector Quantization Algorithm Applied to Automatic Text Classification Tasks. Neural ...
Locally Linear Embedding (LLE), Self-Organizing Map (SOM), Latent Vector Quantization (LVQ), t-Stochastic neighbor embedding (t-SNE) and Uniform Manifold Approximation and Projection (UMAP). DR ...
marktechpost3y
Google AI Proposes a Two-Stage Model that Reconceives Traditional Image Quantization Techniques to Yield Improved Performance on Image Generation and Image Understanding
An algorithm for vector quantization of image data using ViT-VQGAN The Vector ... A low-dimensional latent variable space is projected from the encoder’s output into a linear projection, which allows ...
Frontiers3y
Multivariate Adaptive Step Fruit Fly Optimization Algorithm Optimized Generalized Regression Neural Network for Short-Term Power Load Forecasting
When the algorithm reaches the maximum number of iterations, the location of the fruit fly with best smell concentration is obtained. Then, these optimal parameters will be used in the GRNN to get the ...