• Active Learning with Expected Error Reduction🔍
• Active Boosted Learning 🔍
• How Active Learning Can Train Machine Learning Models with Less ...🔍
• Efficient Multiclass Boosting Classification with Active Learning🔍
• Learning more from less data with active learning🔍
• Improving Probabilistic Models In Text Classification Via Active ...🔍
• Improving Active Learning Performance through the Use of Data ...🔍
• A Survey on Active Learning🔍

Active Learning with Expected Error Reduction

Active learning has been studied extensively as a method for efficient data col- lection. Among the many approaches in literature, Expected Error Reduction ...

Active Boosted Learning (ActBoost)

Active learning deals with the problem of selecting a small subset of examples to la- bel, from a pool of unlabeled data, for train- ing a good classifier.

How Active Learning Can Train Machine Learning Models with Less ...

Throwing more data at a problem isn't always the best answer, and by using AI that is responsible by design, we can reduce these problems while maintaining ...

Efficient Multiclass Boosting Classification with Active Learning

By combining these weak learners based on weighted majority vote, a committee classifier dramatically reduces the training and testing error rates. The ...

Learning more from less data with active learning - J.P. Morgan

By labeling data points that help the quality of the model, teams can identify the samples that are most informative. Using machine learning (ML) models, active ...

Improving Probabilistic Models In Text Classification Via Active ...

Transfer learning is a machine learning technique where knowledge gained from solving one problem is applied to a different but related problem ...

Improving Active Learning Performance through the Use of Data ...

This combination is expected to increase the ML classifier's performance and reduce both the supervisor's involvement and the amount of required ...

A Survey on Active Learning: State-of-the-Art, Practical Challenges ...

Here, with low labeling cost, the active learning (AL) technique could be a solution, whereby a few, high-quality data points are queried by searching for the ...

Active Learning Applications - Schrödinger

Active Learning Applications is a powerful tool that trains a machine learning (ML) model on physics-based data, such as FEP+ predicted affinities or Glide ...

From Linear Classifiers to Overparameterized Neural Networks

The field of Machine Learning (ML) has advanced considerably in recent years ... Active ML aims to address this issue by designing learning ...

What Is Active Learning in Machine Learning? - Revolutionized

One of the most recognizable is natural language processing (NLP). Because NLP models typically require massive datasets and reliability issues ...

Passive and Active Learning in Machine Learning - Pickl.AI

Passive learning involves training models on a fixed dataset, while active learning selects the most informative data points for labelling.

Active Learning vs Machine Learning | Symmetry Electronics

Active learning, on the other hand, represents a unique facet of ML, where the learning process involves interactive querying for data labeling.

Active Learning in machine learning: The AI Revolution No One's ...

Enter active learning. It's the secret sauce that makes machine learning models learn faster, smarter, and with less of that soul-sucking manual ...

ICML 2009 Tutorial Schedule, Sunday June 14

A basic difficulty in applying machine learning in practice is that we often need to solve problems that don't quite match the problems solved by standard ...

The Trouble with Active Learning - By Jaxon AI

Active learning was an important step towards creating effective TDP and cost-sensitive ML, but is it enough?

Active Learning: Less Data, Smarter Models - Labellerr

Active learning empowers machine learning algorithms to become more strategic in their learning process. The core principle lies in enabling the ...

What is Active Learning? - Appen

Active Learning has huge potential to improve the speed of machine learning development efficiently, and make new use cases available. Therefore ...

How Tesla uses Active Learning to elevate it's ML systems

Active Learning is a way to mitigate this problem by reducing the amount of labeled data your model needs. The key idea that AL proposes is that ...

Potentials and Limitations of Active Learning - Weizenbaum Institut

Most research on model emissions focuses on the training phase of a machine-learning model. ... AL is one of many techniques designed to enhance ...