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Machine learning method
Logic learning machine (LLM) is a machine learning method based on the generation of intelligible rules. LLM is an efficient implementation of the Switching
Logic_learning_machine
Overview of and topical guide to machine learning
principal component analysis Learning vector quantization Leabra Linde–Buzo–Gray algorithm Local outlier factor Logic learning machine LogitBoost Manifold alignment
Outline_of_machine_learning
Subset of artificial intelligence
borrowed from statistics, fuzzy logic, and probability theory. There is a close connection between machine learning and compression. A system that predicts
Machine_learning
Topics referred to by the same term
of Laws (Latin: Legum Magister), a postgraduate degree Logic learning machine, a machine learning method Lasalimu language (ISO 639-3 code: llm) Lomlom
LLM_(disambiguation)
Interdisciplinary research area
Quantum machine learning (QML) is the study of quantum algorithms for machine learning. It often refers to quantum algorithms for machine learning tasks
Quantum_machine_learning
AI that learns decision rules from data
Rule-based machine learning (RBML) is a term in computer science intended to encompass any machine learning method that identifies, learns, or evolves
Rule-based_machine_learning
Artificial intelligence and machine learning techniques are used in video games for a wide variety of applications such as non-player character (NPC) control
Machine learning in video games
Machine_learning_in_video_games
Academic journal
Machine Learning. 46: 225–254. doi:10.1023/A:1012470815092. Simon Colton and Stephen Muggleton (2006). "Mathematical Applications of Inductive Logic Programming"
Machine_Learning_(journal)
component analysis Learning vector quantization Leabra Linde–Buzo–Gray algorithm Lloyd's algorithm Local outlier factor Logic learning machine LogitBoost LPBoost
List of artificial intelligence algorithms
List_of_artificial_intelligence_algorithms
Machine learning technique
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
Transfer_learning
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
Methods in artificial intelligence research
His fuzzy logic further provided a means for propagating combinations of these values through logical formulas. Symbolic machine learning approaches
Symbolic artificial intelligence
Symbolic_artificial_intelligence
Type of statistical inference
In logic, statistical inference, and supervised learning, transduction or transductive inference is reasoning from observed, specific (training) cases
Transduction (machine learning)
Transduction_(machine_learning)
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
Artificial intelligence algorithm
A Tsetlin machine is an artificial intelligence algorithm based on propositional logic. A Tsetlin machine is a form of learning automaton collective for
Tsetlin_machine
Categorization of data using statistics
are considered to be possible values of the dependent variable. In machine learning, the observations are often known as instances, the explanatory variables
Statistical_classification
Machine learning paradigm
In machine learning, supervised learning (SL) is a type of machine learning paradigm where an algorithm learns to map input data to a specific output based
Supervised_learning
Intelligence of machines
probabilistic machine learning: "An Inductive Inference Machine". See AI winter § Machine translation and the ALPAC report of 1966. Compared with symbolic logic, formal
Artificial_intelligence
System for reasoning about vagueness
techniques like fuzzy logic (and "less robust" logic) can be applied to learning algorithms. Valiant essentially redefines machine learning as evolutionary
Fuzzy_logic
Professor Emeritus of computer science and engineering (born 1965)
at the University of Washington. He is a researcher in machine learning known for Markov logic network enabling uncertain inference. Domingos received
Pedro_Domingos
Branch of statistics
Wayback Machine." NIPS. 2010. Lopez-Paz, David, et al. "Towards a learning theory of cause-effect inference Archived 13 March 2017 at the Wayback Machine" ICML
Causal_inference
Subdiscipline of artificial intelligence
Artificial Intelligence: Logic, Probability, and Computation", Synthesis Lectures on Artificial Intelligence and Machine Learning" March 2016 ISBN 9781627058414
Statistical relational learning
Statistical_relational_learning
Learning logic programs from data
by Stephen Muggleton in 1990, defined as the intersection of machine learning and logic programming. Muggleton and Wray Buntine introduced predicate invention
Inductive_logic_programming
knowledge is usually represented in a logic-based action description language and used as input for automated planners. Learning action models is important when
Action_model_learning
List of concepts in artificial intelligence
of computer science, Glossary of robotics, Glossary of machine vision, and Glossary of logic. Contents: A B C D E F G H I J K L M N O P Q R S T U V
Glossary of artificial intelligence
Glossary_of_artificial_intelligence
Machine learning method for concept approximation
In machine learning, semantic analysis of a text corpus is the task of building structures that approximate concepts from a large set of documents. It
Semantic analysis (machine learning)
Semantic_analysis_(machine_learning)
study of logic and formal reasoning from antiquity to the present led to the development of the programmable digital computer in the 1940s, a machine predicated
History of artificial intelligence
History_of_artificial_intelligence
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
Method of deriving conclusions
of deriving conclusions from premises. They are integral parts of formal logic, serving as the logical structure of valid arguments. If an argument with
Rule_of_inference
platforms, and tools used for machine learning, deep learning, natural language processing, computer vision, reinforcement learning, artificial general intelligence
Lists of open-source artificial intelligence software
Lists_of_open-source_artificial_intelligence_software
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)
Type of software system
computer systems are reasoning systems in that they all automate some type of logic or decision. In typical use in the Information Technology field however
Reasoning_system
Applications of machine learning to quantum physics
Applying machine learning (ML) (including deep learning) methods to the study of quantum systems is an emergent area of physics research. A basic example
Machine_learning_in_physics
of machine learning (ML) in earth sciences include geological mapping, gas leakage detection and geological feature identification. Machine learning is
Machine learning in earth sciences
Machine_learning_in_earth_sciences
Study of correct reasoning
Logic is the study of correct reasoning. It includes both formal and informal logic. Formal logic is the study of deductively valid inferences or logical
Logic
Artificial neural network algorithm
An artificial neural network's learning rule or learning process is a method, mathematical logic or algorithm which improves the network's performance
Learning_rule
American computer scientist
University of Maryland, College Park. Her primary research interests are in machine learning and reasoning with uncertainty, applied to graphs and structured data
Lise_Getoor
Process of acquiring new knowledge
humans, other animals, and some machines. There is also evidence for some kind of learning in certain plants. Some learning is immediate, induced by a single
Learning
Area of automatic programming
artificial intelligence and programming, which addresses learning of typically declarative (logic or functional) and often recursive programs from incomplete
Inductive_programming
Probabilistic logic
How machine learning is reshaping how we live. pp. 246–7. Richardson, Matthew; Domingos, Pedro (2006). "Markov Logic Networks" (PDF). Machine Learning. 62
Markov_logic_network
Computer system simulating intelligence
application and data clustering in common with fuzzy logic. Generative systems based on deep learning and convolutional neural networks, such as chatGPT
Computational_intelligence
Subfield of artificial intelligence
integrates neural methods (e.g., neural networks and deep learning) with symbolic methods (e.g., formal logic, knowledge representation, and automated reasoning)
Neuro-symbolic_AI
Branch of logic using category theory to study mathematical structures
Categorical logic is the branch of mathematics in which tools and concepts from category theory are applied to the study of mathematical logic. It is also
Categorical_logic
Programming paradigm based on formal logic
Logic programming is a programming, database, and knowledge representation paradigm based on formal logic. A logic program is a set of sentences in logical
Logic_programming
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
Field of artificial intelligence
generators, and classifiers. In a broader sense, parameterized models in machine learning — including neural network architectures such as convolutional neural
Knowledge representation and reasoning
Knowledge_representation_and_reasoning
Probabilistic Soft Logic (PSL) is a statistical relational learning (SRL) framework for modeling probabilistic and relational domains. It is applicable
Probabilistic_soft_logic
Topics referred to by the same term
human-machine interaction using multiple modes of input/output Multimodal therapy, an approach to psychotherapy Multimodal learning, machine learning methods
Multimodal
Automated recognition of patterns and regularities in data
retrieval, bioinformatics, data compression, computer graphics and machine learning. Pattern recognition has its origins in statistics and engineering;
Pattern_recognition
Book by Pedro Domingos
The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World is a book by Pedro Domingos released in 2015. Domingos wrote
The_Master_Algorithm
First three liberal arts of traditional education
is the lower division of the seven liberal arts and comprises grammar, logic, and rhetoric. The trivium is implicit in De nuptiis Philologiae et Mercurii
Trivium
Tool for Advancing Life Sciences) was a Board Management Software machine learning proprietary software developed by Aging Analytics, a company registered
VITAL (machine learning software)
VITAL_(machine_learning_software)
Digital audio workstation
Apple announced and released Logic Pro 11, the first full-number update since 2013. With a heavy emphasis on machine-learning tools, this release introduced
Logic_Pro
Educational software application
programs, materials, or learning and development programs. The learning management system concept emerged directly from e-Learning. Learning management systems
Learning_management_system
Area of machine learning
Rule induction is an area of machine learning in which formal rules are extracted from a set of observations. The rules extracted may represent a full
Rule_induction
Use of artificial intelligence in the automation of electronic design
including machine learning, expert systems, and reinforcement learning. These are used for many tasks, from planning a chip's architecture and logic synthesis
AI-driven_design_automation
Theory of logic to account for observations from quantum theory
In the mathematical study of logic and the physical analysis of quantum foundations, quantum logic is a set of rules for manipulation of propositions
Quantum_logic
Programming paradigm
Luc; Kimmig, Angelika (2015-07-01). "Probabilistic (logic) programming concepts". Machine Learning. 100 (1): 5–47. doi:10.1007/s10994-015-5494-z. ISSN 1573-0565
Probabilistic logic programming
Probabilistic_logic_programming
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
Artificial intelligence control techniques
like neural networks, Bayesian probability, fuzzy logic, machine learning, reinforcement learning, evolutionary computation and genetic algorithms. Intelligent
Intelligent_control
Logic programming using abductive reasoning
achieved (as in normal logic programming). It can be used to solve problems in diagnosis, planning, natural language and machine learning. It has also been
Abductive_logic_programming
U.S. information technology company
2016). "Sumo Logic's new platform powered by machine learning technology". Retrieved 19 June 2019. Mike Vizard (27 November 2017), Sumo Logic Combines Docker
Sumo_Logic
Class of computational model
177–200.. Journal of Symbolic Logic, 38(4):656-657. doi:10.2307/2272014 Simon, Haykin. (2009). Neural Networks and Learning Machines 3rd Edition : Simon Haykin
Data-driven_model
Mathematical model of computation
Transactions on Computational Logic. 1 (1): 77–111. CiteSeerX 10.1.1.146.3017. doi:10.1145/343369.343384. S2CID 2031696. Machine learning using finite-state algorithms
Finite-state_machine
intelligence History of logic (formal reasoning is an important precursor of AI) History of machine learning (timeline) History of machine translation (timeline)
Outline of artificial intelligence
Outline_of_artificial_intelligence
1950 scientific paper by Alan Turing
system based on logic can answer. Turing suggests that humans are too often wrong themselves and pleased at the fallibility of a machine. (This argument
Computing Machinery and Intelligence
Computing_Machinery_and_Intelligence
Supervised machine learning techniques
Structured prediction or structured output learning is an umbrella term for supervised machine learning techniques that involves predicting structured
Structured_prediction
Property of a model
In statistics and machine learning, the bias–variance tradeoff describes the relationship between a model's complexity, the accuracy of its predictions
Bias–variance_tradeoff
Computation model defining an abstract machine
Turing machines, lambda calculus, and other similar formalisms of computation do indeed capture the informal notion of effective methods in logic and mathematics
Turing_machine
Type of machine learning model
and performance via collaborative platforms such as Hugging Face. As machine learning algorithms process numbers rather than text, the text must be converted
Large_language_model
Programmable digital computer used to control machinery
A programmable logic controller (PLC) or programmable controller is an industrial computer that has been ruggedized and adapted for the control of manufacturing
Programmable_logic_controller
Family of formal knowledge representation
are also slides. Jens Lehmann: DL-Learner: Learning concepts in description logics, Journal of Machine Learning Research, 2009. Stefan Heindorf, Lukas Blübaum
Description_logic
Canadian AI researcher and singer
earliest hires at Google Brain in Toronto, working as a machine learning researcher on deep learning and neural network architectures. He worked there from
Nick_Frosst
Concept in computer science
ideally exhibiting this property that is referred to as charge recovery logic, adiabatic circuits, or adiabatic computing (see adiabatic process). Although
Reversible_computing
Interpretation of quantum mechanics
fantasies, since "beneath their apparel of scientific equations or symbolic logic, they are acts of imagination, of 'just supposing'". Theoretical physicist
Many-worlds_interpretation
Logic gate implementing negation
In digital logic, an inverter or NOT gate is a logic gate which implements logical negation. It outputs a bit whose value is opposite of the input bit's
Inverter_(logic_gate)
Force resulting from the quantisation of a field
Approach to the Fermionic Casimir Effect Archived 31 May 2011 at the Wayback Machine" Michael Bordag; Galina Leonidovna Klimchitskaya; Umar Mohideen (2009)
Casimir_effect
also known as synthetic intelligence. Timeline of machine translation Timeline of machine learning Timeline of artificial intelligence risks in global
Timeline of artificial intelligence
Timeline_of_artificial_intelligence
AI accelerator by Nvidia
The NVIDIA Deep Learning Accelerator (NVDLA) is an open-source hardware neural network AI accelerator created by Nvidia. The accelerator is written in
NVDLA
analysis, Pandas for analyzing table data, Scikit-learn for various machine learning tasks, NLTK and spaCy for natural language processing, OpenCV for computer
List of programming languages for artificial intelligence
List_of_programming_languages_for_artificial_intelligence
Processing of natural language by a computer
various commercial applications. Logic translation Translate a text from a natural language into formal logic. Machine translation (MT) Automatically translate
Natural_language_processing
Tree-based ensemble machine learning methods
Boosting – Ensemble learning method Decision tree learning – Machine learning algorithm Ensemble learning – Statistics and machine learning technique Gradient
Random_forest
American computer scientist
– November 18, 2013) was a professor and researcher in the area of machine learning and applications to computational linguistics and computer vision.
Ben_Taskar
Formulation of quantum mechanics
information Quantum key distribution Quantum logic Quantum logic gates Quantum machine Quantum machine learning Quantum metamaterial Quantum metrology Quantum
Path_integral_formulation
Multimethod simulation modeling tool
powerful machine-learning techniques to achieve improved predictive power by combining advanced machine learning algorithms with AnyLogic’s simulation
AnyLogic
Fringe hypothesis
Against Artificial Intelligence Archived 24 February 2021 at the Wayback Machine. Journal of Experimental and Theoretical Artificial Intelligence. Penrose
Quantum_mind
American academic
popularizer of fuzzy logic, neural networks, and noise, and the author of several trade books and textbooks on these and related subjects of machine intelligence
Bart_Kosko
Process of drawing correct inferences
information. Argumentation theory Dialogical logic Epilogism List of rules of inference Transduction (machine learning) Transduction (psychology) Nunes 2011
Logical_reasoning
Assumptions for inference in machine learning
allows a learning algorithm to prioritize one solution (or interpretation) over another, independently of the observed data. In machine learning, the aim
Inductive_bias
Version space learning is a logical approach to machine learning, specifically binary classification. Version space learning algorithms search a predefined
Version_space_learning
Many-valued logic in which truth values comprise a continuous range
In logic, an infinite-valued logic (or real-valued logic or infinitely-many-valued logic) is a many-valued logic in which truth values comprise a continuous
Infinite-valued_logic
Mathematical study of the meaning of programming languages
In programming language theory, semantics is the rigorous mathematical logic study of the meaning of programming languages. Semantics assigns computational
Semantics (programming languages)
Semantics_(programming_languages)
the philosophies of logic and language. Glossary of Linguistic terms. What is I-language? Archived 2011-07-06 at the Wayback Machine – Chapter 1 of I-language:
Philosophy_of_language
Fact that observing a situation changes it
Quantum computing Quantum chaos Decoherence EPR paradox Density matrix Scattering theory Quantum statistical mechanics Quantum machine learning v t e
Observer_effect_(physics)
Japanese computer scientist (born 1936)
artificial neural networks and deep learning. He is currently working part-time as a senior research scientist at the Fuzzy Logic Systems Institute in Fukuoka
Kunihiko_Fukushima
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
Ancient philosophy
traditionally divided into three interconnected disciplines: logic, physics, and ethics. Stoic logic focuses on highly intentional reasoning through propositions
Stoicism
British professor
Society. ILASP (Learning from Answer Sets) is a system which enables learning interpretable knowledge from labelled data using Inductive Logic Programming
Alessandra_Russo
Interpretation of quantum mechanics
inference Credible intervals Degree of belief Doxastic logic Philosophy of science Quantum logic Quantum probability Statistical inference Healey, Richard
QBism
Phenomenon resulting from the superposition of two waves
water waves 1 Java simulation of interference of water waves 2 Flash animations demonstrating interference Archived 2009-06-24 at the Wayback Machine
Wave_interference
LOGIC LEARNING-MACHINE
LOGIC LEARNING-MACHINE
Girl/Female
Indian, Sanskrit
A Yogic Posture
Surname or Lastname
English
English : variant spelling of Lanning.
Surname or Lastname
English
English : variant of Leeming.
Girl/Female
Tamil
Trick, Power, Strategy, Solution by logic, By reasoning
Surname or Lastname
English
English : patronymic from a Germanic personal name beginning with the element gÄ“r, gÄr ‘spear’ (see Geary 2).Probably an Americanized spelling of German Gehring.
Surname or Lastname
English
English : variant spelling of Waring.
Boy/Male
Tamil
Full of feathers, Full of logic, Name of sage, Vatsyayan
Girl/Female
Hindu
Trick, Power, Strategy, Solution by logic, By reasoning
Girl/Female
Tamil
Trick, Power, Strategy, Solution by logic, By reasoning
Girl/Female
Arabic, Muslim, Pashtun
Logic; Reason
Surname or Lastname
English
English : habitational name from Feering, a village in Essex, named from the Old English personal name Fēra + -ingas ‘people of’, i.e. ‘(settlement of) Fēra’s people’.Americanized spelling of German Viering, a topographic name for someone from a swampy area, from a derivative of Germanic vir ‘bog’, ‘swamp’, or a variant of Fehring 2.
Boy/Male
Hindu
Full of feathers, Full of logic, Name of sage, Vatsyayan
Biblical
ploughing plough or till
Surname or Lastname
English
English : unexplained. Probably a respelling of Irish Hearon.Possibly also an altered form of German Haering (see Hering).
Surname or Lastname
English (Dorset and Somerset)
English (Dorset and Somerset) : unexplained.Dutch : patronymic from a short form of the personal name Julianus (see Julian).
Girl/Female
Tamil
Vinyasa | விநà¯à®¯à®¾à®¸
A yogic posture
Vinyasa | விநà¯à®¯à®¾à®¸
Girl/Female
British, English
15th Century
Surname or Lastname
English
English : patronymic from Dear 1.Americanized spelling of German Diering, a variant of Döring (see Doering).
Surname or Lastname
English
English : unexplained.
Girl/Female
Gujarati, Hindu, Indian, Kannada, Tamil
Trick; Power; Strategy; Solution by Logic; By Reasoning
LOGIC LEARNING-MACHINE
LOGIC LEARNING-MACHINE
Biblical
the queen
Girl/Female
French
Blonde.
Boy/Male
Muslim
Messenger
Boy/Male
Indian, Tamil, Telugu
Sage; Lord Shiva; Saint
Boy/Male
Tamil
Niladri | நிலாதà¯à®°à¯€Â
The nilgiris, Blue mountain
Surname or Lastname
English
English : variant of Winkle.Americanized spelling of German Winkels.
Girl/Female
Tamil
Celestial dancer or An Apsara or shakuntalas mother
Boy/Male
American, Australian
From the God Mars
Girl/Female
Hindu
A small creeper
Girl/Female
Hindu, Indian, Traditional
Daughter of Brahma
LOGIC LEARNING-MACHINE
LOGIC LEARNING-MACHINE
LOGIC LEARNING-MACHINE
LOGIC LEARNING-MACHINE
LOGIC LEARNING-MACHINE
pl.
of Earning
n.
The act of gathering after reapers; that which is collected by gleaning.
n.
The act, or state, of inclining; inclination; tendency; as, a leaning towards Calvinism.
n.
A person skilled in logic.
a.
Guiding; directing; controlling; foremost; as, a leading motive; a leading man; a leading example.
n.
The art or process of reasoning; logic.
n.
The parts by which motion imparted to one portion of an engine or machine is transmitted to another, considered collectively; as, the valve gearing of locomotive engine; belt gearing; esp., a train of wheels for transmitting and varying motion in machinery.
n.
The gross amount of the balances adjusted in the clearing house.
n.
The art of reasoning; logic.
n.
The science or art of exact reasoning, or of pure and formal thought, or of the laws according to which the processes of pure thinking should be conducted; the science of the formation and application of general notions; the science of generalization, judgment, classification, reasoning, and systematic arrangement; correct reasoning.
n.
Purport; meaning; intended significance; aspect.
n.
The acquisition of knowledge or skill; as, the learning of languages; the learning of telegraphy.
n.
Logic illustrated by physics.
a.
Giving previous notice; cautioning; admonishing; as, a warning voice.
a.
Of or pertaining to logic; used in logic; as, logical subtilties.
a.
Pertaining to, or designed for, wear; as, wearing apparel.
n.
See Logic.
n.
The act, power, or time of producing or giving birth; as, a tree in full bearing; a tree past bearing.
n.
A treatise on logic; as, Mill's Logic.
n.
The knowledge or skill received by instruction or study; acquired knowledge or ideas in any branch of science or literature; erudition; literature; science; as, he is a man of great learning.