Latest Articles for Machine Learning

Inductive GNNs face privacy threats from link stealing attacks.

A method to assess user trust in AI, especially in healthcare settings.

Researchers use synthetic solar images to improve flare prediction accuracy.

New methods improve audio representation through self-supervised learning techniques.

A new method enhances the efficiency of deep neural networks through automated optimization.

Discover methods to help AI learn continuously without forgetting past knowledge.

A new method improves heart health monitoring through advanced signal processing.

Using GNNs to identify multifunctional proteins enhances biological research.

A study on tracking pet activities with advanced radar methods.

Introducing MemVP to improve efficiency in vision-language models.

A framework to ensure language models provide accurate information.

Learn about methods to find optimal solutions in various fields.

A new method improves DBSCAN's efficiency for high-dimensional datasets and streaming data.

This article discusses efficient learning in multilayer networked dynamical systems.

Introducing sharpness-aware minimization to improve feature construction in genetic programming.

A look into the PDHG algorithm and its role in optimization methods.

This article discusses the design of safe neural network controllers for critical systems.

Aladdin optimizes resource management for efficient LLM inference and improved performance.

Using LLMs to improve adaptation in MLOps.

A new method improving medical data privacy and collaboration between institutions.

This study assesses how well LLMs can identify and classify technical debt.

A new algorithm improves hyperspectral data analysis for astrophysics.

This method combines diffusion models and GANs to generate high-quality data samples effectively.

Examining key aspects of measures in optimization with a focus on optimality conditions.

This study explores Federated Learning's role in Document Visual Question Answering.

This study investigates memory efficiency in large language models through low-rank decomposition.

VSGD combines traditional methods with probabilistic modeling for better deep learning optimization.

A new framework for efficient reinforcement learning in complex environments.

This article discusses enhancing CNNs by leveraging low-frequency information for better resilience against adversarial attacks.

Exploring the benefits and challenges of shared variable embeddings in machine learning.

A quick way to evaluate DNN performance after new training.

A new system for accurate and lightweight real-time piano transcription.

New method improves documentation of AI models and datasets using advanced language models.

Introducing CLAMP, a new method to enhance continual learning across various domains.

Combining SmoothQuant and GPTQ improves efficiency and performance of large language models.

Exploring PETScML's impact on scientific machine learning through second-order methods.

Context Neural Networks improve forecasting accuracy by using related time series insights.

A new approach to enhance contrastive learning through adaptive data augmentation techniques.

A fresh approach improves calculations on the Stiefel manifold for various applications.

RoTHP improves predictions in event modeling through rotary position encoding.