Latest Articles for Machine Learning

Researchers use NeRFs to improve self-driving systems through simulated environments.

Learn how feature attribution explains ranking decisions in automated systems.

A method for generating synthetic data using Bayesian networks to protect privacy while allowing analysis.

Learn how patch pruning boosts the efficiency of deep learning models.

Researchers create a dataset to study how people learn by mimicking others.

ChapTER combines historical context and textual knowledge for improved TKGR performance.

Learn how the MESIA metric improves the quality of code comments.

Using symmetry for better robot learning and performance in real-world tasks.

Innovative protocols enhance machine learning while protecting sensitive data.

This work focuses on improving link prediction accuracy with innovative sampling methods.

Efforts to enhance sentence embeddings for better handling of informal language.

Introducing ZOD-MC, a novel approach for challenging sampling tasks.

Combining Natural Language Inference and concept embeddings improves filling missing knowledge in ontologies.

Combining traditional and deep learning methods enhances image processing efficiency.

A look at how neural networks can model complex functions in various fields.

Introducing TABDet, a new method for detecting backdoor attacks across NLP tasks.

A powerful language model for diverse applications across multiple languages.

This article explores how text elements influence classification tasks in NLP.

A study on how prior knowledge affects LLMs' ability to recognize emotions.

Explore STochastic Gradient Langevin Unlearning for data privacy in machine learning.

PowerGraph enhances analysis of power grid failures through advanced learning techniques.

New methods enhance text generation by focusing on concise, relevant citations.

A new protocol improves the training efficiency of Graph Neural Networks using CPU and GPU.

This article discusses a method for connecting attack behaviors to techniques using MITRE ATTCK.

A new method enhances predictions of geomagnetic changes using machine learning.

A machine learning model provides timely estimates of New Zealand's greenhouse gas emissions.

Tropical neural networks enhance resilience against adversarial attacks in machine learning.

Learn how Bounded Attention enhances image clarity for multiple subjects.

This article examines issues in AI learning due to limited human feedback.

This study compares SES methods for improved lemmatization across multiple languages.

Using neural networks to solve constraints in a gravity model.

A new approach to mix data for better language model performance.

A study highlights data contamination's impact on code model evaluations.

A new method enhances hyperspectral unmixing using deep learning and attention mechanisms.

This research enhances decision-making under uncertainty using batch learning and dynamic strategies.

Introducing GreeDy and CoDy for better clarity in dynamic graph models.

A new method shows variational learning can excel in training complex models.

ProLLM enhances predictions of protein-protein interactions using advanced language models.

This article examines how adversarial attacks alter the learned concepts of CNNs.

DeepKnowledge method improves the reliability of DNNs in critical applications.