David Gerbing from the School of Business at Portland State University introduces lessR, a tool designed to facilitate professional-quality data visualizations and data analysis without programming re ...

Aims To develop prediction models for identifying cases with poor visual outcomes after surgery for primary rhegmatogenous ...

LLM training data mixture optimization breaks when training pools shift — every prior proxy experiment becomes stale.

Large-scale recommendation systems are becoming harder to improve because they no longer operate as isolated models. Modern ...

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.

Most working professionals already understand that AI skills are no longer optional they are a career necessity.

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...

It feels like there’s no escaping AI right now, whether you’re trying to type a sentence without being interrupted by a digital “assistant” or struggling to find a new refrigerator that doesn’t ...

TensorFlow Probability is a library for probabilistic reasoning and statistical analysis in TensorFlow. As part of the TensorFlow ecosystem, TensorFlow Probability provides integration of ...

Objective: Drawing from infodemiology and infoveillance research, this study investigated the patterns of public discourse and message-level drivers of user reactions on X regarding HIV vaccines by ...

Abstract: Linear Regression (LR) is a classical machine learning algorithm which has many applications in the cyber physical social systems (CPSS) to shape and simplify the way we live, work, and ...