Breaking Into The Black Box: Unlocking Meta’s Product-Level Ad Data

Brands can challenge Meta’s automation by surfacing product-level trends, aligning them with purchase behavior, and ...
Proceedings of the National Academy of Sciences (PNAS)

Identifying variation in dinosaur footprints and classifying problematic specimens via unbiased unsupervised machine learning

Machine learning holds great promise for classifying and identifying fossils, and has recently been marshaled to identify trackmakers of dinosaur ...
Science Mission Directorate

NASA AI Model That Found 370 Exoplanets Now Digs Into TESS Data

Trained on data from NASA's exoplanet-hunting missions, the open-source ExoMiner++ deep learning model uses an advanced ...
IEEE

AdaBoost-LSTM: A Hybrid Ensemble Framework for Sequential Credit Card Fraud Detection

Abstract: Credit card fraud detection is a critical task in financial systems, requiring effective algorithms to accurately classify transactions as fraudulent or non-fraudulent. This paper proposes a ...
UMass Lowell

Ph.D. Dissertation Proposal Defense in Electrical and Computer Engineering: Masoumeh Farhadi Nia 11/7

Brain–Computer Interfaces (BCIs) enable direct communication between the brain and external devices, offering new pathways for independent mobility among individuals with severe motor impairments. In ...
GitHub

TreeSHAP-compatible AdaBoost and RUSBoost classifiers for explainable AI on imbalanced datasets.

This package provides custom implementations of AdaBoost and RUSBoost classifiers that are compatible with SHAP's TreeExplainer, enabling fast local explanations for boosting algorithms on imbalanced ...
Healio

Real-world dermatology dataset reveals flaws of some AI diagnostic algorithms

Please provide your email address to receive an email when new articles are posted on . AI algorithms to diagnose skin cancer had lower sensitivity and specificity when tested on a multimodal, ...
Scientific Research Publishing

A Comparative Study of Ensemble Learning Techniques and Classification Models to Identify Phishing Websites ()

The advent of the internet, as we all know, has brought about a significant change in human interaction and business operations around the world; yet, this evolution has also been marked by security ...
Scientific Research Publishing

Adane, K., Beyene, B. and Abebe, M. (2023) Single and Hybrid-Ensemble Learning-Based Phishing Website Detection: Examining Impacts of Varied Nature Datasets and Informative ...

ABSTRACT: The advent of the internet, as we all know, has brought about a significant change in human interaction and business operations around the world; yet, this evolution has also been marked by ...