Latest Articles for Data Science

A new method improves object state recognition using knowledge graphs.

Exploring the need for fairness in mobile technology and algorithms.

A new approach to maintain fairness in machine learning clustering algorithms.

Introducing a new method for efficient Wasserstein distance computation in large datasets.

New methods enhance the calibration of neural networks trained on distilled datasets.

A new framework enhances predictions in healthcare using summary statistics.

Exploring how item removal affects recommendations in sequential systems.

A new method improves learning speed in machine learning algorithms.

TransFusion improves the generation of high-quality long-sequence synthetic time-series data.

A framework for understanding changing systems through data-driven techniques.

Examining how specific functions can perfectly reconstruct random variables.

Examining the gap between model performance and real-world conditions.

A new framework enhances fairness in algorithms using uncertain demographic information.

A look at quantization methods and their applications using the Cantor distribution.

An overview of structured missingness in health research and its implications.

A look at how one-step methods and critic regularization enhance RL performance.

New self-supervised methods improve predictions of future actions in videos.

A new method enhances translation accuracy for low-resource languages.

Open-source toolkit enhances Raman spectroscopy analysis across various studies.

A look into deep learning's key components and their interactions.

This study focuses on enhancing GNNs to overcome challenges from biased training data.

PG-RCNN improves 3D object detection accuracy using LiDAR technology.

A new framework improves robustness of Graph Contrastive Learning against structural attacks.

New research reveals the capabilities of Sumformer in improving Transformer efficiency.

This study examines how pre-training data affects model robustness in various tasks.

New methods improve accuracy in medical report generation using knowledge graphs and smart training.

A new method enhances image transformations for better accuracy and efficiency.

This article examines how to assess AI models in healthcare by considering uncertainty in diagnosis.

Investigating fairness in ML systems considering multiple protected attributes.

Exploring a novel approach to regression using quantum computing.

This study compares methods for handling high-cardinality categorical variables in machine learning.

Exploring the potential of hybrid quantum-classical GANs in data generation and classification.

Investigating vulnerabilities of DNNs against adversarial noise in image denoising.

Techniques for improving machine translation through effective data strategies.

A new method enhances unsupervised graph learning through entropy estimation and subset sampling.

A study on SCS versus traditional convolutional layers in image classification.

Learn how ensemble learning improves prediction accuracy despite noise.

A look into cascade systems and strategies for better predictions.

This article examines how generative images can improve visual recognition tasks.

Feature selection simplifies data analysis by identifying key variables.