Latest Articles for Data Science

A new method to enhance data collection efficiency in sensor networks.

A new model efficiently targets nodes in GNNs with minimal changes.

RENT improves model performance by using resampling techniques with noisy labels.

This article examines how initial conditions affect random neural networks' behavior.

High-quality image-text pairs improve performance of multimodal models in various tasks.

A benchmark dataset enhances machine learning for better tornado detection.

A new method improves event argument extraction in complex documents.

A new dataset to assess planning skills of language models in real-life tasks.

A new method improves calibration in multi-class classification efficiently.

New methods improve cancer detection using AI without needing extensive labeled data.

A method to enhance model performance across diverse data groups.

Using synthetic training data to enhance efficiency in detecting terminal strips.

Examining learning efficiencies of heavy-tailed algorithms and their generalization properties.

A look at the importance of aligning AI systems with human values.

This article discusses Stochastic Gradient Flow and its impact on model learning.

Examining how data augmentation techniques affect model performance across different classes.

A new approach improves disease prediction using electronic health records.

New methods enhance DNN robustness against adversarial attacks by considering example vulnerabilities.

This study improves code models using compiler intermediate representations for better multilingual performance.

ProbSAINT predicts used car prices while assessing uncertainty in predictions.

A new method for consistent counterfactual explanations despite model changes.

This study examines how contextual knowledge enhances the detection of adverse drug events.

MolNexTR improves recognition of chemical structures from images with advanced techniques.

A new framework improves item suggestions by balancing social influence and user preferences.

Research sheds light on transfer learning applications and model performance relationships.

A tool for improving forecasting accuracy using counterfactuals and data visualization.

A fast and efficient method for graph processing without complex models.

A fresh approach for assessing neural networks without extensive training.

A new method improves memory efficiency in training large language models on consumer hardware.

A new approach to enhance recommendation systems by improving accuracy and diversity.

This article presents new filtering techniques for better economic modeling.

Exploring how network depth impacts learning and generalization in AI.

A new approach improves data sampling in complex physical systems.

New techniques improve segmentation accuracy in chest radiographs.

Research reveals how flat minima relate to better model performance on unseen data.

This article discusses new methods for improving few-shot learning performance.

A fresh approach to estimating how training data impacts model predictions.

Learn how ADMM efficiently solves distributed optimization problems.

A new method enhances memory for better decision-making in RL agents.

Automated methods improve efficiency in extracting information from Knowledge Graphs.