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Bias vs variance explained: Avoid overfitting in ML

What is overfitting and underfitting in machine learning? What is Bias and Variance? Overfitting and Underfitting are two common problems in machine learning and Deep learning. If a model has low ...
Scientific Research Publishing

Multimodal Digital Phenotyping for Bipolar Disorder: Robust Mood-State Classification and Early Relapse Risk Monitoring ()

Bipolar Disorder, Digital Phenotyping, Multimodal Learning, Face/Voice/Phone, Mood Classification, Relapse Prediction, T-SNE, Ablation Share and Cite: de Filippis, R. and Al Foysal, A. (2025) ...
techxplore

Overparameterized neural networks: Feature learning precedes overfitting, research finds

Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, structureless data. Yet when trained on datasets with structure, they learn the ...
Polygon

Valve is cutting corners with Steam Machine to compete with the current consoles

Just how powerful will the Steam Machine be? Based on expert analysis of the specs revealed by Valve when it announced the Steam Machine on Wednesday, its new compact, console-like gaming PC is aimed ...
IGN

Steam Machine Hands-On: First Impressions of Valve’s New Console-Like Gaming PC

Steam Machines are back for the first time since Valve teamed up with manufacturers like Alienware and Lenovo back in the 2010s. But while those original console-PC hybrids failed because of a lack of ...
IEEE

Summary Graph Induced Invariant Learning for Generalizable Graph Learning

Abstract: As a promising strategy to achieve generalizable graph learning tasks, graph invariant learning emphasizes identifying invariant subgraphs for stable predictions on biased unknown ...
The Verge

OpenAI gets caught vibe graphing

CEO Sam Altman called a strange graph in its GPT-5 presentation a ‘mega chart screwup.’ CEO Sam Altman called a strange graph in its GPT-5 presentation a ‘mega chart screwup.’ is a senior reporter ...
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Regularization In Deep Learning — The Real Cure For Overfitting

Regularization in Deep Learning is very important to overcome overfitting. When your training accuracy is very high, but test accuracy is very low, the model highly overfits the training dataset set ...
IEEE

When Machine Learning Meets Knowledge Graph: A New Vision for Designing Network Intelligent Optimization Pipelines and Rules

Abstract: With the continuous development of mobile communication networks, machine learning (ML) significantly saves on labor costs and enhances the efficiency of network operations and maintenance ...