Machine learning rediscovers equations governing ocean biogeochemistry

Climate and ocean models use a series of equations to represent complex natural processes. However, the equations used in ...
Frontiers

AI & Machine Learning for Injury Prediction: From Data to Preventive Strategies

The integration of AI and Machine Learning into injury prediction is transforming how researchers, clinicians, and sports ...

New Memo: Microsoft’s Nadella Argues Learning Loops Beat Models

Microsoft CEO Nadella argues learning loops beat picking the best AI model. Here's what a learning loop is, why it builds a ...
Journal of Medical Internet Research

Using Domain Adaptation and Inductive Transfer Learning to Improve Patient Outcome Prediction in the Intensive Care Unit: Retrospective Observational Study

Furthermore, domain adaptation (DA) has been the most common TL method in general, whereas inductive transfer learning (ITL) has been rare. To the best of our knowledge, DA and ITL have never been ...
IEEE

Generalized SMO Algorithm for SVM-Based Multitask Learning

Abstract: Exploiting additional information to improve traditional inductive learning is an active research area in machine learning. In many supervised-learning applications, training data can be ...
IEEE

Group-Sparse Inductive Matrix Completion Through Transfer Learning

Abstract: The emergence of big data has enabled the creation of significant models by allowing the storage of large data volumes. Transfer learning is a machine learning technique that transfers ...
GitHub

Easy Few-Shot Learning

Ready-to-use code and tutorial notebooks to boost your way into few-shot image classification. This repository is made for you if: you're new to few-shot learning and want to learn; or you're looking ...
Harvard Business Review

How to Win with Machine Learning

And how to catch up if you’re lagging behind by Ajay Agrawal, Joshua Gans and Avi Goldfarb The past decade has brought tremendous advances in an exciting dimension of artificial intelligence—machine ...
www.cs.utexas.edu

Raymond J. Mooney

B.S. in Computer Engineering, University of Illinois at Urbana/Champaign, 1983 M.S. in Computer Science, University of Illinois at Urbana/Champaign, 1985 See my invited talk at the EMNLP 2023 Big ...
Nature

Learning high-level visual representations from a child’s perspective without strong inductive biases

Young children develop sophisticated internal models of the world based on their visual experience. Can such models be learned from a child’s visual experience without strong inductive biases? To ...