Visual Studio Magazine

Support Vector Regression with SGD Training Using C#

Support vector regression can predict numeric values effectively, and this article shows how to implement and train a kernel SVR model in C# using stochastic sub-gradient descent.

Toward experiment-guided AlphaFold: Researchers overcome AI tool's single-conformation limitation

The AI-based program AlphaFold predicts a protein's 3D structure with remarkable accuracy. However, it tends to reduce heterogeneous structures to a single dominant conformation, or shape, and ...
GitHub

Angular Penalty Softmax Losses Pytorch

(Note: the SphereFace implementation is not exactly as described in their paper but instead uses the 'trick' presented in the ArcFace paper to use arccosine instead of the double angle formula) There ...
GitHub

A Neural Network Architecture Combining Gated Recurrent Unit (GRU) and Support Vector Machine (SVM) for Intrusion Detection

This is an accepted paper at the 10th International Conference on Machine Learning and Computing (ICMLC) in Macau, China on February 26-28, 2018. The full paper on this project may be read at ...
Scientific Research Publishing

Speech Emotion Recognition Based on CNN-Transformer with Different Loss Function ()

Speech Emotion Recognition (SER) is crucial for enhancing human-computer interactions by enabling machines to understand and respond appropriately to human emotions. However, accurately recognizing ...
IEEE

A Hardware-Friendly Alternative to Softmax Function and Its Efficient VLSI Implementation for Deep Learning Applications

Abstract: The Softmax function holds an essential role in most machine learning algorithms. Conventional realization of Softmax necessitates computationally intensive exponential operations and ...