Litcius/Paper detail

Survey on Meta Learning Algorithms for Few Shot Learning

Madhava Gaikwad, Ashwini Doke

20222022 6th International Conference on Intelligent Computing and Control Systems (ICICCS)14 citationsDOI

Abstract

In Meta learning auto learning algorithms are applied to machine learning experiments. The Meta learning is trying to solve problem of learning to learn as there is a significant lack in data as well as experts. There are many novel approaches developed in field of meta learning in past few years. This paper is summary of ongoing research in field of meta learning. It describes current trends and development in field of meta learning and with tactic knowledge how the meta learning can be applied to achieve few shot learning. It is believe that the Meta learning will perform well to overcome the challenges of few shot learning.

Topics & Concepts

Meta learning (computer science)Computer scienceArtificial intelligenceMachine learningInstance-based learningActive learning (machine learning)Field (mathematics)Learning classifier systemRobot learningLearning to learnUnsupervised learningMulti-task learningTask (project management)PsychologyMathematics educationMathematicsEngineeringRobotSystems engineeringPure mathematicsMobile robotDomain Adaptation and Few-Shot LearningCOVID-19 diagnosis using AIMachine Learning and ELM