Latest Articles for Machine Learning

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.

A novel approach improves distance optimization strategies at singular points.

This paper discusses methods to learn system dynamics using limited and noisy data effectively.

Efficiently managing large data through low-rank tensor-train approximation techniques.

Examining fairness in reinforcement learning systems for ethical decision-making.

This study assesses GPT-4V's performance on low-level chart tasks.

A new framework enhances AI's grasp of 3D spaces.

Examining the effects of machine learning systems on human behavior and fairness.

This study presents a model combining text and demographic data for better recommendations.

This study examines speech features to improve early diagnosis of Parkinson's disease.

A fresh approach to enhance self-supervised learning using binning in tabular data.

A study on predicting composite material behavior using advanced neural networks.

A new approach combines machine learning and physics for better material analysis.

CaFA brings efficiency and accuracy to global weather predictions with machine learning.

A new approach enhances precipitation simulations for better climate response.

This article examines the impact of neural networks on data shape and classification.

Introducing a fixed-point method for learning causal relationships without complex graphs.

Analyzing Twitter bios using large language models for effective text clustering.

Combining static and dynamic analysis improves bug prediction accuracy in software development.

A new method for improving model structures more effectively and efficiently.

A new approach to enhance client availability in federated learning.

A look at the risks adversarial machine learning poses to autonomous spacecraft.

Galaxies reveal their history through morphology and star formation activity.

Advancements in explainable AI enhance understanding of complex ML models.

Explore gradient flow techniques to enhance ResNet training and performance.

MuDet enhances vehicle detection using color images and height maps.