Curriculum learning is a technique in machine learning in which a model is trained on examples of increasing difficulty, where the definition of "difficulty"...

In education, a curriculum (/kəˈrɪkjʊləm/; pl.: curriculums or curricula /kəˈrɪkjʊlə/) is the totality of student experiences that occur in an educational...

standard curriculum. Learning should be an enjoyable act where children should feel that they are valued and their voices are heard. The curriculum structure...

Reinforcement learning is one of the three basic machine learning paradigms, alongside supervised learning and unsupervised learning. Reinforcement learning differs...

their interests. The goal is to create meaningful learning experiences for the children. Emergent curriculum can be practiced with children at any grade level...

In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a computational model inspired by the structure...

The transformer is a deep learning architecture based on the multi-head attention mechanism, in which text is converted to numerical representations called...

International Conference on Machine Learning (ICML) is a leading international academic conference in machine learning. Along with NeurIPS and ICLR, it is...

In statistics and machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from...

Multimodal learning is a type of deep learning that integrates and processes multiple types of data, referred to as modalities, such as text, audio, images...

Q-learning is a reinforcement learning algorithm that trains an agent to assign values to its possible actions based on its current state, without requiring...

In machine learning, attention is a method that determines the importance of each component in a sequence relative to the other components in that sequence...

Mamba is a deep learning architecture focused on sequence modeling. It was developed by researchers from Carnegie Mellon University and Princeton University...

Decision tree learning is a supervised learning approach used in statistics, data mining and machine learning. In this formalism, a classification or...

expectations. Any type of learning experience may include unintended lessons. However, the concept of a hidden curriculum often refers to knowledge gained...

Self-supervised learning (SSL) is a paradigm in machine learning where a model is trained on a task using the data itself to generate supervisory signals...

Temporal difference (TD) learning refers to a class of model-free reinforcement learning methods which learn by bootstrapping from the current estimate...

The International Conference on Learning Representations (ICLR) is a machine learning conference typically held in late April or early May each year....

Statistical learning theory is a framework for machine learning drawing from the fields of statistics and functional analysis. Statistical learning theory...

distinct from the elementary and high school "integrated curriculum" movement. Integrative Learning comes in many varieties: connecting skills and knowledge...

Machine learning is included in the CFA Curriculum (discussion is top-down); see: Kathleen DeRose and Christophe Le Lanno (2020). "Machine Learning" Archived...

whose middle layer contains recurrent connections that change by a Hebbian learning rule.: 73–75  Later, in Principles of Neurodynamics (1961), he described...

Transfer learning (TL) is a technique in machine learning (ML) in which knowledge learned from a task is re-used in order to boost performance on a related...

computational learning theory, probably approximately correct (PAC) learning is a framework for mathematical analysis of machine learning. It was proposed...

In machine learning, reinforcement learning from human feedback (RLHF) is a technique to align an intelligent agent with human preferences. It involves...

Active learning is a special case of machine learning in which a learning algorithm can interactively query a human user (or some other information source)...

In machine learning, support vector machines (SVMs, also support vector networks) are supervised max-margin models with associated learning algorithms...

"edtech". Educational technology for learning management systems (LMS), such as tools for student and curriculum management, and education management...

In statistics and machine learning, leakage (also known as data leakage or target leakage) is the use of information in the model training process which...

Competency-based learning, and skill development and training. Educational approaches such as Early Intensive Behavioral Intervention, curriculum-based measurement...