In machine learning, multiple-instance learning (MIL) is a type of supervised learning. Instead of receiving a set of instances which are individually...

pharmaceuticals. Federated learning aims at training a machine learning algorithm, for instance deep neural networks, on multiple local datasets contained...

In machine learning, multi-label classification or multi-output classification is a variant of the classification problem where multiple nonexclusive...

Multi-task learning Multilinear subspace learning Multimodal learning Multiple instance learning Multiple-instance learning Never-Ending Language Learning Offline...

learning efficiency. Since transfer learning makes use of training with multiple objective functions it is related to cost-sensitive machine learning...

of distance learning. This is the first known instance of the use of materials for independent language study. The concept of e-learning began developing...

Deep learning is a subset of machine learning that focuses on utilizing neural networks to perform tasks such as classification, regression, and representation...

as materials science. For instance, graph neural networks (GNNs) have demonstrated their capability in scaling deep learning for the discovery of new stable...

possible values of the dependent variable. In machine learning, the observations are often known as instances, the explanatory variables are termed features...

test instance to be generated by the model. Robot learning is inspired by a multitude of machine learning methods, starting from supervised learning, reinforcement...

machines. An alternative approach uses multiple-instance learning by encoding molecules as sets of data instances, each of which represents a possible molecular...

rote learning eschews comprehension, so by itself it is an ineffective tool in mastering any complex subject at an advanced level. For instance, one illustration...

Search MPEG-7 Multimedia information retrieval Multiple-instance learning Nearest neighbor search Learning to rank Content-based Multimedia Information...

learner has learned is an instance of meaningful learning. Utilization of meaningful learning may trigger further learning, as the relation of a concept...

Reinforcement learning is one of the three basic machine learning paradigms, alongside supervised learning and unsupervised learning. Q-learning at its simplest...

Instantaneously trained neural networks Latent semantic indexing Multiple-instance learning Naive Bayes classifier Natural language processing approaches...

algorithm to correctly determine output values for unseen instances. This requires the learning algorithm to generalize from the training data to unseen...

machine learning and statistical classification, multiclass classification or multinomial classification is the problem of classifying instances into one...

implicit and explicit learning; for instance, research on amnesia often shows intact implicit learning but impaired explicit learning. Another difference...

personally participate in this specific type of learning course. In a prior pharmaceutics course, for instance, a mere 34.6% of the 19 students initially preferred...

parsed into sub-types. For instance, declarative memory comprises both episodic and semantic memory. Non-associative learning refers to "a relatively permanent...

Dissociative identity disorder (DID), previously known as multiple personality disorder (MPD), is one of multiple dissociative disorders in the DSM-5, ICD-11, and...

manner. Functional genomics and computational approaches based on multiple instance learning have also been developed to integrate RNA-seq data to predict...

Multiple disabilities is a term for a person with a combination of disabilities, for instance, someone with both a sensory disability and a motor disability...

referred to as problem-based learning, experiential learning and 21st century learning. It is supported by the work of learning theorists and psychologists...

psychologists have argued that this "is not an instance of learning styles, rather, it is an instance of ability appearing as a style". Likewise, Fleming...

courses, training programs, or learning and development programs. Adaptive learning systems have previously been used, for instance, to help students develop...

Weak supervision (also known as semi-supervised learning) is a paradigm in machine learning, the relevance and notability of which increased with the...

Meta-learning is a subfield of machine learning where automatic learning algorithms are applied to metadata about machine learning experiments. As of...

viewed learning as interacting with incentives in the environment. For instance, Ute Holzkamp-Osterkamp viewed motivation as interconnected with learning. Lev...