Google’s new AI training method helps small models tackle complex reasoning

Google's SRL framework provides a step-by-step "curriculum" that makes LLMs more reliable for complex reasoning tasks.
The Lancet

Development and validation of a machine-learning model to reduce futile procurements in donations after circulatory death in liver transplantation in the USA…

We show that, compared with surgeon predictions and existing risk-prediction tools, our machine-learning model can enhance ...
Physics World

Physicists discuss the future of machine learning and artificial intelligence

IOP Publishing’s Machine Learning series is the world’s first open-access journal series dedicated to the application and ...
IEEE

Unsupervised/Semi-Supervised Magnetic Anomaly Detection Method Based on Deep Support Vector Data Description

Abstract: Existing magnetic anomaly detection (MAD) methods are widely categorized into target-, noise-, and machine learning-based methods. This article first analyzes the commonalities and ...
marktechpost

Prefix-RFT: A Unified Machine Learning Framework to blend Supervised Fine-Tuning (SFT) and Reinforcement Fine-Tuning (RFT)

Large language models are typically refined after pretraining using either supervised fine-tuning (SFT) or reinforcement fine-tuning (RFT), each with distinct strengths and limitations. SFT is ...
Frontiers

Advanced Supervised Machine Learning Techniques for Accurate Prediction of Diabetes Mellitus Using Feature Selection

The final, formatted version of the article will be published soon. Background): Diabetes Mellitus (DM) is a chronic metabolic disorder that poses a significant global health challenge, affecting ...
Scientific Research Publishing

Ileberi, E., Sun, Y. and Wang, Z. (2021) Performance Evaluation of Machine Learning Methods for Credit Card Fraud Detection Using SMOTE and Adaboost. IEEE Access, 9, 165286-165294.

ABSTRACT: SQL injection attacks pose a critical threat to web application security, exploiting vulnerabilities to gain access, or modify sensitive data. Traditional rule-based and machine learning ...
C&EN

Historical Data Mining Deep Dive into Machine Learning-Aided 2D Materials Research in Electrochemical Applications

You are free to share (copy and redistribute) this article in any medium or format and to adapt (remix, transform, and build upon) the material for any purpose, even commercially within the parameters ...
Frontiers

Advances in machine learning for the detection and characterization of microplastics in the environment

1 Department of Environmental Sciences, Jahangirnagar University, Dhaka, Bangladesh 2 Division of Translational Cancer Research, Department of Laboratory Medicine, Lund University, Lund, Sweden ...