Latest Articles for Data Science

A look at how graph learning enhances semi-supervised domain adaptation.

A new method leverages graphs for better medical image analysis.

A new approach combines machine learning with traditional methods for solving complex math problems.

GCA-HNG improves model training by creating challenging negative samples.

A new framework addresses action bias in video understanding.

Examining the impact of hardware and communication on deep learning efficiency.

Discover how Aureus transforms news reading with smart recommendations.

Discover the vibrant world of tropical geometry and its unique concepts.

Learn how prescriptive analytics shapes decision-making across various sectors.

A look at how TinTeM improves AI learning with smarter methods.

AbilityLens standardizes evaluation for multimodal large language models.

Discover how data augmentation can improve NER models in low-resource domains.

A new technique for identifying unusual data points effectively.

Examining adversarial attacks and promoting fairness through mixup training.

An overview of how model size and data affect learning in deep neural networks.

A new method adjusts learning rates for faster and better model training.

Understanding how Knowledge Graphs can reduce false information in AI responses.

New strategies enhance GNN performance in multi-label node classification tasks.

Discover how federated learning enhances activity recognition while addressing data challenges.

A look into how various distance measurements impact shapes and data.

This article explores how a simple transformer learns the one-nearest neighbor prediction method.

A look into graph generation and its significance in connecting the world.

A new method simplifies medical image labeling using just one annotated slice.

Explore a new method combining labeled and unlabeled data for efficient 3D modeling.

A new method improves how we generate and understand conditional distributions.

New methods tackle challenges in identifying weak classes within federated learning.

Discover how schedule-free optimization transforms machine learning efficiency.

Research shows data can improve college admission success rates.

Examining the issue of sycophancy in large language models and its implications.

A new training approach enhances model learning by mixing easy and hard examples.

Explabox simplifies machine learning for everyone, ensuring transparency and fairness in AI models.

A fresh method to understand causal relationships in dynamic environments.

Exploring the use of RTDETR for safer roads in Bangladesh.

A look at bias in AI and how to tackle it fairly.

Using galaxies' relationships, a GNN predicts dark matter halo masses more accurately than traditional methods.

Using synthetic data to improve facial emotion recognition accuracy in machines.

A new method generates realistic data for training models in identity verification.

A simple overview of PL and LS constants in optimization and data analysis.

Using LLMs to classify and promote green practices on social media.

This research improves Knowledge Graphs using refined negative sampling techniques for better model performance.