Abstract: This paper presents a novel method for reducing the dimensionality of kernel spaces. Recently, to maintain the convexity of training, log linear models without mixtures have been used as ...

Attention-based architectures are a powerful force in modern AI. In particular, the emergence of in-context learning abilities enables task generalization far beyond the original next-token prediction ...

Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States ...

Add a description, image, and links to the log-linear-learning topic page so that developers can more easily learn about it.

A variety of linear models are available to represent common active electronic devices such as transistors and vacuum tubes. Devices operating under large-signal conditions often require nonlinear ...

AssemblyAI updates its Speaker Diarization model for better accuracy and multilingual support, alongside new tutorials for developers. AssemblyAI has recently unveiled significant updates to its ...

Prior to PILOT, fitting linear model trees was slow and prone to overfitting, especially with large datasets. Traditional regression trees struggled to capture linear relationships effectively. Linear ...

To address the limitations of commonly used cross-validation methods, the linear regression method (LR) was proposed to estimate population accuracy of predictions based on the implicit assumption ...

Create a Tutorials folder under FastEddy-models with examples and notebooks sub-folders. Move the contents from FastEddy-tutorials example and notebooks folders here. Finally create a Zenodo ...