Large Language Models Get All the Hype, but Small Models Do the Real Work

For many tasks in corporate America, it’s not the biggest and smartest AI models, but the smaller, more simplistic ones that ...
Harvard Business Review

When Working With AI, Act Like a Decision-Maker—Not a Tool-User

While AI can create space for higher-order thinking, it can also tempt us to outsource that thinking altogether. Good ...
Scientific Research Publishing

Estimating Average and Heterogeneous Effects of Special Education: A Causal Machine Learning Perspective ()

Causal Machine Learning (CML) unites ML techniques with CI in order to take advantage of both approaches’ strengths. CML ...
The Commonwealth

Commonwealth of Learning champions alternative educational models to fuel inclusive growth

Education, particularly open and distance learning, has long been associated with increasing educational access, bridging the digital divide, as well as advancing the social and economic development ...
Frontiers

Interpretable machine learning model to predict 90-day radiographically confirmed pneumonia after chemotherapy initiation in non-Hodgkin lymphoma: development and internal ...

1 Department of Hematology, Dongyang Hospital Affiliated with Wenzhou Medical University, Jinhua, China 2 Department of Central Laboratory, Affiliated Hangzhou First People’s Hospital, School of ...
GitHub

An AutoML framework for classical machine learning algorithms, automating model selection and hyperparameter tuning through Bayesian optimization, portfolio-based meta-learning ...

Start a Ray head node Connect and start Ray worker nodes via SSH Activate virtual environments and configure PYTHONPATH on all nodes 📌 Before running the script, ensure passwordless SSH access from ...
Scientific Research Publishing

Mohammadagha, M. (2025) Hyperparameter Optimization Strategies for Tree-Based Machine Learning Models Prediction: A Comparative Study of Ada-Boost, Decision Trees, and Random ...

ABSTRACT: This study presents a comprehensive and interpretable machine learning pipeline for predicting treatment resistance in psychiatric disorders using synthetically generated, multimodal data.
Frontiers

Machine learning models for predicting the risk of depressive symptoms in Chinese college students

1 Department of Psychology/Research Center of Adolescent Psychology and Behavior, School of Education, Guangzhou University, Guangzhou, Guangdong, China 2 School of Psychology, South China Normal ...
IEEE

Hyperparameter Selection Methods for Machine Learning Models for Predicting Big Five Test

Abstract: This study addresses the optimization of hyperparameter selection in machine learning models designed to predict psychological characteristics (e.g., “Big Five” traits) from social media ...