Accelerated learning by active example selection
Related Experiment Video
Updated: Oct 9, 2026

Automated Interactive Video Playback for Studies of Animal Communication
Published on: February 9, 2011
1AI Division, Institute for Computer Science, University of Bonn, Germany.
Abstract:
Much previous work on training multilayer neural networks has attempted to speed up the backpropagation algorithm using more sophisticated weight modification rules, whereby all the given training examples are used in a random or predetermined sequence. In this paper we investigate an alternative approach in which the learning proceeds on an increasing number of selected training examples, starting with a small training set. We derive a measure of criticality of examples and present an incremental learning algorithm that uses this measure to select a critical subset of given examples for solving the particular task. Our experimental results suggest that the method can significantly improve training speed and generalization performance in many real applications of neural networks. This method can be used in conjunction with other variations of gradient descent algorithms.
More Related Videos
11:20Recording Single Neurons' Action Potentials from Freely Moving Pigeons Across Three Stages of Learning
Published on: June 2, 2014
08:05Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques
Published on: June 30, 2020
Related Concept Videos
Introduction to Learning
In contrast to learned behaviors, unlearned behaviors such as crying, sexual...
Associative Learning
Classical conditioning, also known...
Cognitive Learning
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
Purposive Learning
Observational Learning
Steps in the Modeling Process
Attention is the first necessary component for observational learning. It involves focusing on what the model is doing and saying. For example, if you decide to take a drawing class to enhance your skills, you need to pay close attention to the instructor's words and hand movements. The characteristics of the model significantly...