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Type of supervised learning in machine learning
In machine learning, multiple-instance learning (MIL) is a type of supervised learning. Instead of receiving a set of instances which are individually
Multiple_instance_learning
Overview of and topical guide to machine learning
Multi-task learning Multilinear subspace learning Multimodal learning Multiple instance learning Multiple-instance learning Never-Ending Language Learning Offline
Outline_of_machine_learning
Classification problem where multiple labels may be assigned to each instance
In machine learning, multi-label classification or multi-output classification is a variant of the classification problem where multiple nonexclusive
Multi-label_classification
Branch of machine learning
In machine learning, deep learning (DL) focuses on utilizing multilayered neural networks to perform tasks such as classification, regression, and representation
Deep_learning
Subset of artificial intelligence
test instance being generated by the model. Robot learning is inspired by a multitude of machine learning methods, starting from supervised learning, reinforcement
Machine_learning
Largely debunked theories that aim to account for differences in individuals' learning
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
Learning_styles
Process of categorizing documents
Instantaneously trained neural networks Latent semantic indexing Multiple-instance learning Naive Bayes classifier Natural language processing approaches
Document_classification
Machine learning technique
learning efficiency. Since transfer learning makes use of training with multiple objective functions it is related to cost-sensitive machine learning
Transfer_learning
Machine learning paradigm
algorithm towards correct predictions. For instance, if you want a model to identify cats in images, supervised learning would involve feeding it many images
Supervised_learning
Decentralized machine learning
pharmaceuticals. Federated learning aims at training a machine learning algorithm, for instance deep neural networks, on multiple local datasets contained
Federated_learning
Fundamental unit of cognition
mechanisms include associative learning, in which similarities are gradually noticed as learners encounter instances, and hypothesis testing, which involves
Concept
Method of image retrieval
Search MPEG-7 Multimedia information retrieval Multiple-instance learning Nearest neighbor search Learning to rank Content-based Multimedia Information
Content-based_image_retrieval
Memorization technique based on repetition
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
Rote_learning
Field of machine learning
Reinforcement learning is one of the three basic machine learning paradigms, alongside supervised learning and unsupervised learning. While supervised learning and
Reinforcement_learning
Predictive chemical model
machines. An alternative approach uses multiple-instance learning by encoding molecules as sets of data instances, each of which represents a possible molecular
Quantitative structure–activity relationship
Quantitative_structure–activity_relationship
Mental illness with multiple personality states
Dissociative identity disorder (DID), previously known as multiple personality disorder (MPD), is a dissociative disorder characterized by the presence
Dissociative identity disorder
Dissociative_identity_disorder
Process of acquiring new knowledge
choose specific topics/skills or jobs to learn and the styles of learning. For instance, children may not have developed consolidated interests, ethics
Learning
Educational software application
of distance learning. This is the first known instance of the use of materials for independent language study. The concept of e-learning began to develop
Learning_management_system
Categorization of data using statistics
possible values of the dependent variable. In machine learning, the observations are often known as instances, the explanatory variables are termed features
Statistical_classification
Process by which a gene can code for multiple proteins
manner. Functional genomics and computational approaches based on multiple instance learning have also been developed to integrate RNA-seq data to predict
Alternative_splicing
Tasks in machine learning
In machine learning, a common task is the study and construction of algorithms that can learn from and make predictions on data. Such algorithms function
Training, validation, and test data sets
Training,_validation,_and_test_data_sets
Machine learning technique
In machine learning, reinforcement learning from human feedback (RLHF) is a technique to align an intelligent agent with human preferences. It involves
Reinforcement learning from human feedback
Reinforcement_learning_from_human_feedback
Research field that lies at the intersection of machine learning and computer security
synthetic data. As machine learning is scaled, it often relies on multiple computing machines. In federated learning, for instance, edge devices collaborate
Adversarial_machine_learning
Type of artificial neural network
these early efforts did not lead to a working learning algorithm for hidden units, i.e., deep learning. In 1965, Alexey Grigorevich Ivakhnenko and Valentin
Feedforward_neural_network
American biomedical engineer (born 1976)
Z., Madabhushi, A., Gao, P., Cong, F., & Lu, C. (2025). When multiple instance learning meets foundation models: Advancing histological whole slide image
Anant_Madabhushi
Generalized neurodevelopmental disorder
Intellectual disability (ID), also known as general learning disability (in the United Kingdom), and formerly as mental retardation (in the United States)
Intellectual_disability
Table layout for visualizing performance; also called an error matrix
sounds. In machine learning these matrices show the success of the learning system both in supervised learning and unsupervised learning, where they are
Confusion_matrix
Study of viral material
of virus-host associations using protein language models and multiple instance learning". PLOS Computational Biology. 20 (11) e1012597. bioRxiv 10.1101/2023
Virome_analysis
Research field in deep learning
deep learning (TDL) is a research field that extends deep learning to handle complex, non-Euclidean data structures. Traditional deep learning models
Topological_deep_learning
Automated recognition of patterns and regularities in data
provided, consisting of a set of instances that have been properly labeled by hand with the correct output. A learning procedure then generates a model
Pattern_recognition
Type of learning
learner has learned is an instance of meaningful learning. Utilization of meaningful learning may trigger further learning, as the relation of a concept
Meaningful_learning
Distance education using mobile device technology
M-learning, or mobile learning, is a form of distance education or technology enhanced active learning where learners use portable devices such as mobile
M-learning
Computational model used in machine learning
In machine learning, a neural network (NN) or neural net, is a computational model inspired by the structure and functions of biological neural networks
Neural network (machine learning)
Neural_network_(machine_learning)
Paradigm in machine learning
Weak supervision (also known as semi-supervised learning) is a paradigm in machine learning, the relevance and notability of which increased with the
Weak_supervision
Computerized information extraction from images
models constructed with the aid of geometry, physics, statistics, and learning theory. The scientific discipline of computer vision is concerned with
Computer_vision
Type of associative learning process for behavioral modification
even longer delay before behavior extinction due to the learning factor of repeated instances becoming necessary to get reinforcement, when compared with
Operant_conditioning
Set of methods for supervised statistical learning
In machine learning, a support vector machine (SVM) or support vector network is a supervised max-margin model with associated learning algorithms that
Support_vector_machine
associated costs Cost-sensitive machine learning introduces a scalar cost function in order to find one (of multiple) Pareto optimal points in this multi-objective
Cost-sensitive machine learning
Cost-sensitive_machine_learning
Set of learning techniques in machine learning
In machine learning (ML), feature learning or representation learning is a set of techniques that allow a system to automatically discover the representations
Feature_learning
Nested Multi-Instance Learning". arXiv:1602.08033 [cs.SI]. Buza, Krisztian. "Feedback prediction for blogs."Data analysis, machine learning and knowledge
List of datasets for machine-learning research
List_of_datasets_for_machine-learning_research
Erroneous AI-generated content
hallucinations arise from a tension between novelty and usefulness. For instance, Amabile and Pratt define human creativity as the production of novel and
Hallucination (artificial intelligence)
Hallucination_(artificial_intelligence)
Relationship between proficiency and experience
a learning curve Proficiency (test score)Experience (hours spent)01234503691215Proficiency (test score)Example of a steep learning curve A learning curve
Learning_curve
Term in educational psychology
Concept learning, also known as category learning, concept attainment, and concept formation, is defined by Bruner, Goodnow, & Austin (1956) as "the search
Concept_learning
Use of technology in education to enhance learning and teaching
practice of educational approaches to learning. Educational technology as technological tools and media, for instance massive online courses, that assist
Educational_technology
Chinese-American computer scientist
2006. Yixin Chen, Jinbo Bi and James Z. Wang, MILES: Multiple-Instance Learning via Embedded Instance Selection, IEEE Transactions on Pattern Analysis and
James_Z._Wang
Educational learning method using computer algorithms and AI
courses, training programs, or learning and development programs. Adaptive learning systems have previously been used, for instance, to help students develop
Adaptive_learning
Ongoing, voluntary, and self-motivated pursuit of knowledge
Lifelong learning is the "ongoing, voluntary, and self-motivated" pursuit of learning for either personal or professional reasons. Lifelong learning is important
Lifelong_learning
Use of multiple antennas in radio
Multiple-input and multiple-output (MIMO) (/ˈmaɪmoʊ, ˈmiːmoʊ/) is a wireless technology that multiplies the capacity of a radio link using multiple transmit
MIMO
Subfield of machine learning
categorized as three main problems in the book Preference Learning: In label ranking, the model has an instance space X = { x i } {\displaystyle X=\{x_{i}\}\,\
Preference_learning
Instructional strategy and a type of blended learning
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
Flipped_classroom
Subfield of machine learning
Meta-learning is a subfield of machine learning where automatic learning algorithms are applied to metadata about machine learning experiments. As of
Meta-learning (computer science)
Meta-learning_(computer_science)
Flaw in mathematical modelling
possible to reconstruct details of individual training instances from an overfitted machine learning model's training set. This may be undesirable if, for
Overfitting
Type of machine learning model
training dataset. A mixture of experts (MoE) is a machine learning architecture in which multiple specialized neural networks ("experts") work together,
Large_language_model
Study of psychological theories of learning
viewed learning as interacting with incentives in the environment. For instance, Ute Holzkamp-Osterkamp viewed motivation as interconnected with learning. Lev
Psychology_of_learning
Process of learning better perception skills
in some cases, there is an overlap between perceptual learning and category learning. For instance, to discriminate between two items, a categorical difference
Perceptual_learning
Diagnostic plot of binary classifier ability
increasingly used in machine learning and data mining research. A classification model (classifier or diagnosis) is a mapping of instances between certain classes/groups
Receiver operating characteristic
Receiver_operating_characteristic
Structuring text as input to generative artificial intelligence
model to perform in-context learning can be viewed as an instance of the more general learning-to-learn or meta-learning paradigm Quantifying Language
Prompt_engineering
AI whose outputs can be understood by humans
(XAI), generally overlapping with interpretable AI or explainable machine learning (XML), is a field of research that explores methods that provide humans
Explainable artificial intelligence
Explainable_artificial_intelligence
Learning that occurs through observing the behaviour of others
Observational learning is learning that occurs through observing the behavior of others. It is a form of social learning which takes various forms, based
Observational_learning
Method of machine learning
In computer science, online machine learning is a method of machine learning in which data becomes available in a sequential order and is used to update
Online_machine_learning
Multiple hypotheses explain the possible connections between sleep and learning in humans. Research indicates that sleep does more than allow the brain
Sleep_and_learning
This is a list of datasets for machine learning research. It is part of the list of datasets for machine-learning research. These datasets consist primarily
List of datasets in computer vision and image processing
List_of_datasets_in_computer_vision_and_image_processing
Range of neurodevelopmental conditions
Learning disability, primarily learning disorder, or learning difficulty (British English) is a condition in the brain that causes difficulties comprehending
Learning_disability
Piece of information about the content of an image
to a certain application. This is the same sense as feature in machine learning and pattern recognition generally, though image processing has a very sophisticated
Feature_(computer_vision)
Computer technology related to computer vision and image processing
related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or
Object_detection
System to predict users' preferences
and other deep-learning-based approaches. The recommendation problem can be seen as a special instance of a reinforcement learning problem whereby the
Recommender_system
Function that is tied to a particular instance or class
class-based programming, methods are defined within a class, and objects are instances of a given class. One of the most important capabilities that a method
Method_(computer_programming)
Vector quantization algorithm minimizing the sum of squared deviations
whereas only the geometric median minimizes Euclidean distances. For instance, better Euclidean solutions can be found using k-medians and k-medoids
K-means_clustering
Machine-learning process
More generally, grammatical inference is that branch of machine learning where the instance space consists of discrete combinatorial objects such as strings
Grammar_induction
Process of replacing missing data with substituted values
multiple imputation use machine learning techniques to improve its performance. MIDAS (Multiple Imputation with Denoising Autoencoders), for instance
Imputation_(statistics)
Type of machine learning method
to be confused with the lazy learning regime, see Neural tangent kernel). In machine learning, lazy learning is a learning method in which generalization
Lazy_learning
Deep learning method
A generative adversarial network (GAN) is a class of machine learning frameworks and a prominent framework for approaching generative artificial intelligence
Generative adversarial network
Generative_adversarial_network
Real-time observability platform
over 800 integrations for metrics collection, log management, machine learning-based anomaly detection, and AI-assisted troubleshooting. The company behind
Netdata
Pedagogical approach
Computer-supported collaborative learning (CSCL) is a pedagogical approach wherein learning takes place via social interaction using a computer or through
Computer-supported collaborative learning
Computer-supported_collaborative_learning
Type of feedforward neural network
network with two learning layers. Backpropagation was independently developed multiple times in early 1970s. The earliest published instance was Seppo Linnainmaa's
Multilayer_perceptron
Class of artificial neural network
expensive online variant is called "Real-Time Recurrent Learning" or RTRL, which is an instance of automatic differentiation in the forward accumulation
Recurrent_neural_network
Machine learning technique
Gradient boosting is a machine learning technique based on boosting in a functional space, where the target is pseudo-residuals instead of residuals as
Gradient_boosting
Concept on humans' and animals' use of past learning in present situations
notion of discrimination learning. Generalization is understood to be directly tied to the transfer of knowledge across multiple situations. The knowledge
Generalization_(learning)
Measurement of algorithmic bias
Fairness in machine learning (ML) refers to the various attempts to correct algorithmic bias in automated decision processes based on ML models. Decisions
Fairness_(machine_learning)
Data model
Learning Object Metadata is a data model, usually encoded in XML, used to describe a learning object and similar digital resources used to support learning
Learning_object_metadata
Optimization algorithm
become an important optimization method in machine learning. Both statistical estimation and machine learning consider the problem of minimizing an objective
Stochastic_gradient_descent
Example of the learning curve effect on performance
distributions and shapes of learning curves: A test of the instance theory of automaticity. Journal of Experimental Psychology: Learning, Memory, and Cognition
Power_law_of_practice
Channel access method used by various radio communication technologies
Code-division multiple access (CDMA) is a channel access method used by various radio communication technologies. CDMA is an example of multiple access, where
Code-division_multiple_access
Paradigm in machine learning that uses no classification labels
are added on to enable new capabilities or removed to make learning faster. For instance, neurons change between deterministic (Hopfield) and stochastic
Unsupervised_learning
Learning style
Visual learning is one of the learning styles in which information is primarily received and understood by a learner when presented in a visual format
Visual_learning
prejudice. For instance, Walker and Crogan reclassified a Jigsaw class as a control class after the Jigsaw technique failed in this class. Learning by teaching
Jigsaw_(teaching_technique)
Self-directed, iterative learning approach
For instance, agile problem-based learning is a pedagogical and curricular vehicle used to blur the work-study silos, informal and formal learning spaces
Agile_learning
Use of multiple languages
display and currency; but each instance of the system only supports a single locale. Multilingualised software supports multiple languages for display and
Multilingualism
Mathematical problem in cryptography
In cryptography, learning with errors (LWE) is a mathematical problem that is widely used to create secure encryption algorithms. It is based on the idea
Learning_with_errors
Machine learning algorithm
Decision tree learning is a supervised learning approach used in statistics, data mining and machine learning. In this formalism, a classification or
Decision_tree_learning
Programming which all objects are created by classes
or with all objects of that class. Object state can differ between each instance of the class whereas the class state is shared by all of them. The object
Class_(programming)
Generalization of definite integrals to functions of multiple variables
multivariable calculus), a multiple integral is a definite integral of a function of several real variables, for instance, f(x, y) or f(x, y, z). Integrals
Multiple_integral
Method in education
assessment for learning, including diagnostic testing, is a range of formal and informal assessment procedures conducted by teachers during the learning process
Formative_assessment
Process in which a first language is being acquired
learning mechanism could explain a wide range of language structure acquisition phenomena. Statistical learning theory suggests that, when learning language
Language_acquisition
Method for discovering interesting relations between variables in databases
Association rule learning is a rule-based machine learning method for discovering interesting relations between variables in large databases. It is intended
Association_rule_learning
Machine learning that combines deep learning and reinforcement learning
Deep reinforcement learning (deep RL) is a subfield of machine learning that combines reinforcement learning (RL) and deep learning. RL considers the problem
Deep_reinforcement_learning
Deep learning generative model to encode data representation
In machine learning, a variational autoencoder (VAE) is an artificial neural network architecture introduced by Diederik P. Kingma and Max Welling in 2013
Variational_autoencoder
Framework or philosophy for effective teaching
Records, student interest surveys, and multiple intelligence or learning style inventories. Assessment for learning includes diagnostic (or pre-assessment)
Differentiated_instruction
How people learn from experience
be completed to give learning that will change behaviour. The cycle can be performed multiple times to build up layers of learning. Honey and Mumford gave
Learning_cycle
Network protocol that builds a loop-free logical topology for Ethernet networks
each instance. Each instance can be assigned a number of configured VLANs and frames assigned to these VLANs operate in this spanning tree instance whenever
Spanning_Tree_Protocol
MULTIPLE INSTANCE-LEARNING
MULTIPLE INSTANCE-LEARNING
Boy/Male
Hebrew
God will multiply.
Boy/Male
Hindu, Indian, Tamil
Multiple
Boy/Male
Hebrew American Latin
God will multiply.
Female
English
English form of Latin Constantia, CONSTANCE means "steadfast."Â
Boy/Male
Muslim
Multiple lights. Luster.
Girl/Female
Arabic, Muslim
Example; Instance; Precedent
Boy/Male
Hebrew
God will multiply.
Boy/Male
Hebrew
God will multiply.
Boy/Male
Hebrew
God shall multiply.
Girl/Female
American, Australian, British, Christian, Dutch, English, French, German, Latin, Portuguese, Shakespearean, Swedish
Constancy; Steadfastness
Boy/Male
Hebrew Spanish
God will multiply.
Girl/Female
Latin American English French Shakespearean
Firm of purpose. Constancy, from the Latin Constantia.
Female
English
Variant spelling of English/Scottish Anstice, ANSTACE means "resurrection."
Boy/Male
Australian, Vietnamese
Many; Multiple
Female
French
French form of Latin Constantia, CUSTANCE means "steadfast."Â
Surname or Lastname
English and French
English and French : from the medieval female personal name Constance, Latin Constantia, originally a feminine form of Constantius (see Constant), but later taken as the abstract noun constantia ‘steadfastness’.English and French : habitational name from Coutances in La Manche, France, which was named Constantia in Latin (see above) in honor of the Roman emperor Constantius Chlorus, who was responsible for fortifying the settlement in ad 305.
Boy/Male
Hebrew
God will multiply.
Boy/Male
Hebrew Spanish
God will multiply.
Boy/Male
Hebrew
God will multiply.
Boy/Male
Hindu, Indian
Un Countable; Multiple; Countless
MULTIPLE INSTANCE-LEARNING
MULTIPLE INSTANCE-LEARNING
Girl/Female
Australian, Danish, Dutch, French, German, Hebrew, Swedish
God May Protect; Female Version of Jakoh; Supplanter
Male
Iranian/Persian
(جهان) Persian name JAHAN means "world."
Female
Polish
Polish form of Hebrew Yehuwdiyth, JUDYTA means "Jewess" or "praised."
Girl/Female
Indian
Boy/Male
Australian, Farsi, Irish, Latin
Vain; He who Guards the Treasure; Curly-headed
Girl/Female
Hebrew
Sparkle.
Boy/Male
Indian, Punjabi, Sikh
Quiet; Gentle
Girl/Female
Tamil
Large settlement
Boy/Male
Arabic, Muslim
Inventor; Creator
Boy/Male
Hindu
Moon crested Lord
MULTIPLE INSTANCE-LEARNING
MULTIPLE INSTANCE-LEARNING
MULTIPLE INSTANCE-LEARNING
MULTIPLE INSTANCE-LEARNING
MULTIPLE INSTANCE-LEARNING
v. t.
To place at a distance or remotely.
n.
That which is instant or urgent; motive.
imp. & p. p.
of Instance
a.
Manifold; multiple.
a.
A natural aptitude or knack; a predilection; as, an instinct for order; to be modest by instinct.
n.
Instance; urgency.
a.
Having many flues; as, a multiflue boiler. See Boiler.
v. t.
To impress, as an animating power, or instinct.
n.
One who, or that which, multiplies or increases number.
n.
The number by which another number is multiplied. See the Note under Multiplication.
v. t.
To outstrip by as much as a distance (see Distance, n., 3); to leave far behind; to surpass greatly.
a.
Used by, or appropriated to, insane persons; as, an insane hospital.
n.
The number by which another number is multiplied; a multiplier.
v. t.
To add (any given number or quantity) to itself a certain number of times; to find the product of by multiplication; thus 7 multiplied by 8 produces the number 56; to multiply two numbers. See the Note under Multiplication.
n.
The act or quality of being instant or pressing; urgency; solicitation; application; suggestion; motion.
a.
Immediately; instantly; at once; as, he left instanter.
a.
A day of the present or current month; as, the sixth instant; -- an elliptical expression equivalent to the sixth of the month instant, i. e., the current month. See Instant, a., 3.
imp. & p. p.
of Multiply
v. t.
To mention as a case or example; to refer to; to cite; as, to instance a fact.
n.
The act of issuing, or giving out; as, the issuance of an order; the issuance of rations, and the like.