Machine Learning Model

Machine learning models aim to create systems that can learn from data and make predictions or decisions without explicit programming. Current research emphasizes improving model accuracy, interpretability, and robustness, focusing on architectures like deep neural networks, decision tree ensembles, and transformer models, as well as exploring decentralized learning and techniques for mitigating biases and vulnerabilities. These advancements are crucial for diverse applications, ranging from optimizing resource management (e.g., smart irrigation) to improving healthcare diagnostics and enhancing the security and trustworthiness of AI systems.

998papers

Papers

May 6, 2025

Algorithmic Accountability in Small Data: Sample-Size-Induced Bias Within Classification Metrics
Jarren Briscoe, Garrett Kepler, Daryl Deford, Assefaw Gebremedhin
Washington State University
Small Datasets Classification Metric New Metric Machine Learning Model Absolute Stance Bias

May 3, 2025

BOOM: Benchmarking Out-Of-distribution Molecular Property Predictions of Machine Learning Models
Evan R. Antoniuk, Shehtab Zaman, Tal Ben-Nun, Peggy Li, James Diffenderfer, Busra Demirci, Obadiah Smolenski, Tim Hsu, Anna M. Hiszpanski+3
Lawrence Livermore National Laboratory●Binghamton University
Molecular Foundation Model Machine Learning Model Novel Molecule Molecular Property Prediction

May 2, 2025

Machine Learning Fairness in House Price Prediction: A Case Study of America's Expanding Metropolises
Abdalwahab Almajed, Maryam Tabar, Peyman Najafirad
Imam Abdulrahman Bin Faisal University●The University of Texas at San Antonio
Bias Mitigation Machine Learning Fairness House Price Prediction United State Case Study Urban Environment Machine Learning Model

May 1, 2025

Development of an Adapter for Analyzing and Protecting Machine Learning Models from Competitive Activity in the Networks Services
Denis Parfenov, Anton Parfenov
Research Institute of Digital Intelligent Technologies●Orenburg State University
Supervised Autoencoder Remote Human Operator Secure Machine Learning Network Traffic Network Programming Long Short Range Adapter Machine Learning Model

April 29, 2025

Waymo Driverless Car Data Analysis and Driving Modeling using CNN and LSTM
Aashish Kumar Misraa, Naman Jain, Saurav Singh Dhakad
Columbia Universtiy
Main CAR Sale Factor Autonomous Vehicle CNN Network Human Accuracy LSTM Network Machine Learning Model

April 27, 2025

April 26, 2025

Performance of Machine Learning Classifiers for Anomaly Detection in Cyber Security Applications
Markus Haug, Gissel Velarde
IU International University of Applied Sciences
Anomaly Detection Machine Learning Model Generative Adversarial Network Generative Model Security Application System Performance Machine Learning Classifier Extreme Gradient Boosting

April 23, 2025

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models
Mathias Hanson, Gregory Lewkowicz, Sam Verboven
Vrije Universiteit Brussel●Universit´ e Libre de Bruxelles - Smart Law Hub●FARI - AI for the Common Good Institute
Machine Translation Model Development Model Alignment Position Engineering Machine Learning Model Technical Indicator

April 22, 2025

Cost-Effective Text Clustering with Large Language Models
Hongtao Wang, Taiyan Zhang, Renchi Yang, Jianliang Xu
Hong Kong Baptist University●ShanghaiTech University●Institute of Computing Technology
Contextual Embeddings Language Model Machine Learning Model Cost Effective Text Clustering

April 21, 2025

Is Intelligence the Right Direction in New OS Scheduling for Multiple Resources in Cloud Environments?
Xinglei Dou, Lei Liu, Limin Xiao
BeihangUniversity
Cognitive Intelligence Cloud Environment Machine Learning Model Task Scheduling Cloud Service New Resource

April 16, 2025

April 15, 2025

Counterfactual Fairness Evaluation of Machine Learning Models on Educational Datasets
Woojin Kim, Hyeoncheol Kim
Korea University
Algorithmic Fairness Counterfactual Fairness Machine Learning Model Group Fairness

April 12, 2025

Regretful Decisions under Label Noise
Sujay Nagaraj, Yang Liu, Flavio P. Calmon, Berk Ustun
University of Toronto●UC Santa Cruz●Harvard SEAS●UC San Diego
Label Noise Noisy Label Real World Noisy Datasets Machine Learning Model

April 11, 2025

Machine Learning Model

Papers

Algorithmic Accountability in Small Data: Sample-Size-Induced Bias Within Classification Metrics

BOOM: Benchmarking Out-Of-distribution Molecular Property Predictions of Machine Learning Models

Machine Learning Fairness in House Price Prediction: A Case Study of America's Expanding Metropolises

Development of an Adapter for Analyzing and Protecting Machine Learning Models from Competitive Activity in the Networks Services

Waymo Driverless Car Data Analysis and Driving Modeling using CNN and LSTM

Test Set Sizing for the Ridge Regression

Reliable Thermal Monitoring of Electric Machines through Machine Learning

Performance of Machine Learning Classifiers for Anomaly Detection in Cyber Security Applications

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models

Cost-Effective Text Clustering with Large Language Models

Is Intelligence the Right Direction in New OS Scheduling for Multiple Resources in Cloud Environments?

Enhancing Stroke Diagnosis in the Brain Using a Weighted Deep Learning Approach

Sliced-Wasserstein Distance-based Data Selection

Fine Flood Forecasts: Incorporating local data into global models through fine-tuning

Leveraging Machine Learning Models to Predict the Outcome of Digital Medical Triage Interviews

The Balancing Act of Policies in Developing Machine Learning Explanations

Counterfactual Fairness Evaluation of Machine Learning Models on Educational Datasets

Regretful Decisions under Label Noise

Application of machine learning models to predict the relationship between air pollution, ecosystem degradation, and health disparities and lung cancer in Vietnam

A Survey of Machine Learning Models and Datasets for the Multi-label Classification of Textual Hate Speech in English