An ai could learn the optimal hyperparameters, architecture, and even dataset. This article will introduce you to the meta learning in detail. Meta learning, an original concept of cognitive psychology, is now applied to machine learning techniques. Instead of manually defining metafeatures, we can also learn a joint representa. Having finite time in which to learn means that humans have to be able to make the most of each piece of data available to them, building and then drawing upon a. Another popular view of meta learning decomposes the model update into two stages.
Meta learning takes this idea one step further, rather than finetuning according to one downsteam task, it optimizes the model to be good at many, if not all. Remarkably, once trained, it can learn new tasks quickly from only a few examples fewshot learning. Piaget argues that learning develops in stages and children develop cognitive strategies as they move through those stages. A classifier is the learner model, trained for operating a given task. The weights of the prior tasks can again be defined via the accuracy of the surrogate model or via relative landmarks. The term comes from the meta prefixs modern meaning of an abstract recursion, or x about x, similar to its use in metaknowledge, metamemory, and meta emotion overview. Meta learning is a subfield of machine learning where automatic learning algorithms are applied on metadata about machine learning experiments. Meta learning is a relatively new direction in the field of artificial intelligence and is considered to be the key to realizing general artificial intelligence. This view is problematic as the metalearner is now a. Here are the five meta skills we all need to succeed in the newmillennium talent marketplace.
Metalearning, or learning to learn, is the science of systematically observing. This is akin to how human experts start a manual search for good models. In higher stages, children should use meta thinking strategies to achieve abstract thought and reach conclusion on difficult topics. Metalearning by adjusting priors based on extended pac. The st is the state representation of the meta learner at time step t. More recently, the partnership for 21st century skills has identified selfdirected learning as one of the life and career skills necessary to prepare students for postsecondary education and the workforce. If we go by the social psychology definition, meta learning is the state of being aware of and taking control of ones own learning. Educational psychologists have long promoted the importance of metacognition for regulating and supporting student learning. Metacognition is a regulatory system that helps a person understand and control his or her own cognitive performance. Meta learning is a recent technique to overcome, i.
How to quickly and easily understand the essence of meta learning. Understand standard strategies for parallelization. Maudsley 1979 as the process by which learners become aware. It involves awareness of how they learn, an evaluation of their learning needs, generating strategies to meet these. The field of metalearning has as one of its primary goals the understanding of the interaction between the mechanism of learning and the concrete contexts in which that mechanism is applicable. Semantic scholar extracted view of metalearning a tutorial by christophe g. As of 2017 the term had not found a standard interpretation, however the main goal is to use such metadata to understand how automatic learning can become flexible in solving learning problems, hence to. It aims at using machine learning itself to automatically learn the most appropriate algorithms and parameters for a. Pdf metalearning concepts and techniques researchgate. Metacognition allows people to take charge of their own learning.