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.

Changing AI math could reduce the hardware burden, researchers show

Sophisticated AI models tend to require a lot of memory and take up a lot of storage space. One of the ways to reduce that ...
IEEE

ERVQ: Leverage Residual Vector Quantization for Speech Emotion Recognition

Abstract: Although speech pre-trained models (PTM) have shown remarkable performance in speech emotion recognition (SER), they are constructed for general tasks and exhibit limitations in capturing ...
Occupational Health & Safety

Vector Solutions Puts Responsible AI and Gamified Training at the Forefront of Workplace Safety

The company is combining human-reviewed AI tools with interactive, gamified learning to improve safety training, incident ...
IEEE

Learning Based CSI Look Up Table: A Novel Vector Quantization Approach for High Accuracy CSI Reconstruction

Abstract: To fully exploit the benefits of spatial multiplexing gains within Frequency Division Duplex (FDD) Multiple-Input Multiple-Output (MIMO) systems, the development of a robust Channel State ...
Network World

Tether is shipping TurboQuant KV-cache quantization with Vulkan support into its QVAC SDK

The latest release of qvac-fabric-llm.cpp, the inference engine of the QVAC Fabric LLM, features TurboQuant integration for resource management in long-running inference sessions. Tether adopts the ...