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Deep learning is a subset of machine learning that focuses on utilizing multilayered neural networks to perform tasks such as classification, regression, and representation learning. The field takes inspiration from biological neuroscience and is centered around stacking artificial neurons into layers and "training" th... | Wikipedia/Deep_neural_network |
Computer-aided detection (CADe), also called computer-aided diagnosis (CADx), are systems that assist doctors in the interpretation of medical images. Imaging techniques in X-ray, MRI, endoscopy, and ultrasound diagnostics yield a great deal of information that the radiologist or other medical professional has to analy... | Wikipedia/Automated_medical_diagnosis |
In the field of artificial intelligence (AI), alignment aims to steer AI systems toward a person's or group's intended goals, preferences, or ethical principles. An AI system is considered aligned if it advances the intended objectives. A misaligned AI system pursues unintended objectives.
It is often challenging for A... | Wikipedia/AI_control_problem |
Nature Methods is a monthly peer-reviewed scientific journal covering new scientific techniques. It was established in 2004 and is published by Springer Nature under the Nature Portfolio. Like other Nature journals, there is no external editorial board and editorial decisions are made by an in-house team, although peer... | Wikipedia/Nature_Methods |
In machine learning and computer vision, M-theory is a learning framework inspired by feed-forward processing in the ventral stream of visual cortex and originally developed for recognition and classification of objects in visual scenes. M-theory was later applied to other areas, such as speech recognition. On certain ... | Wikipedia/M-theory_(learning_framework) |
Mutation is a genetic operator used to maintain genetic diversity of the chromosomes of a population of an evolutionary algorithm (EA), including genetic algorithms in particular. It is analogous to biological mutation.
The classic example of a mutation operator of a binary coded genetic algorithm (GA) involves a proba... | Wikipedia/Mutation_(genetic_algorithm) |
The term citizen science (synonymous to terms like community science, crowd science, crowd-sourced science, civic science, participatory monitoring, or volunteer monitoring) is research conducted with participation from the general public, or amateur/nonprofessional researchers or participants of science, social scienc... | Wikipedia/Citizen_Science |
Algorithmic transparency is the principle that the factors that influence the decisions made by algorithms should be visible, or transparent, to the people who use, regulate, and are affected by systems that employ those algorithms. Although the phrase was coined in 2016 by Nicholas Diakopoulos and Michael Koliska abou... | Wikipedia/Algorithmic_transparency |
IBM SPSS Modeler is a data mining and text analytics software application from IBM. It is used to build predictive models and conduct other analytic tasks. It has a visual interface which allows users to leverage statistical and data mining algorithms without programming.
One of its main aims from the outset was to eli... | Wikipedia/SPSS_Modeler |
Machine learning control (MLC) is a subfield of machine learning, intelligent control, and control theory which aims to solve optimal control problems with machine learning methods. Key applications are complex nonlinear systems for which linear control theory methods are not applicable.
== Types of problems and task... | Wikipedia/Machine_learning_control |
In deep learning, pruning is the practice of removing parameters from an existing artificial neural network. The goal of this process is to reduce the size (parameter count) of the neural network (and therefore the computational resources required to run it) whilst maintaining accuracy. This can be compared to the biol... | Wikipedia/Pruning_(artificial_neural_network) |
Predictive modelling uses statistics to predict outcomes. Most often the event one wants to predict is in the future, but predictive modelling can be applied to any type of unknown event, regardless of when it occurred. For example, predictive models are often used to detect crimes and identify suspects, after the crim... | Wikipedia/Predictive_modeling |
The core idea of artificial intelligence systems integration is making individual software components, such as speech synthesizers, interoperable with other components, such as common sense knowledgebases, in order to create larger, broader and more capable A.I. systems. The main methods that have been proposed for int... | Wikipedia/Artificial_intelligence_systems_integration |
Applications of machine learning (ML) in earth sciences include geological mapping, gas leakage detection and geological feature identification. Machine learning is a subdiscipline of artificial intelligence aimed at developing programs that are able to classify, cluster, identify, and analyze vast and complex data set... | Wikipedia/Machine_learning_in_earth_sciences |
In representation learning, knowledge graph embedding (KGE), also called knowledge representation learning (KRL), or multi-relation learning, is a machine learning task of learning a low-dimensional representation of a knowledge graph's entities and relations while preserving their semantic meaning. Leveraging their e... | Wikipedia/Knowledge_graph_embedding |
A dynamic Bayesian network (DBN) is a Bayesian network (BN) which relates variables to each other over adjacent time steps.
== History ==
A dynamic Bayesian network (DBN) is often called a "two-timeslice" BN (2TBN) because it says that at any point in time T, the value of a variable can be calculated from the intern... | Wikipedia/Dynamic_Bayesian_network |
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 book in order to generate interest from people outside the field.
== Overview ==
The book outlines five approaches of machine learning: inductive reasoning, conn... | Wikipedia/The_Master_Algorithm |
Crossover in evolutionary algorithms and evolutionary computation, also called recombination, is a genetic operator used to combine the genetic information of two parents to generate new offspring. It is one way to stochastically generate new solutions from an existing population, and is analogous to the crossover that... | Wikipedia/Crossover_(genetic_algorithm) |
Tomographic reconstruction is a type of multidimensional inverse problem where the challenge is to yield an estimate of a specific system from a finite number of projections. The mathematical basis for tomographic imaging was laid down by Johann Radon. A notable example of applications is the reconstruction of computed... | Wikipedia/Tomographic_reconstruction |
In statistics, a generalized linear model (GLM) is a flexible generalization of ordinary linear regression. The GLM generalizes linear regression by allowing the linear model to be related to the response variable via a link function and by allowing the magnitude of the variance of each measurement to be a function of ... | Wikipedia/Generalised_linear_model |
NeuroSolutions is a neural network development environment developed by NeuroDimension. It combines a modular, icon-based (component-based) network design interface with an implementation of advanced learning procedures, such as conjugate gradients, the Levenberg-Marquardt algorithm, and back-propagation through time. ... | Wikipedia/NeuroSolutions |
Decision tree learning is a supervised learning approach used in statistics, data mining and machine learning. In this formalism, a classification or regression decision tree is used as a predictive model to draw conclusions about a set of observations.
Tree models where the target variable can take a discrete set of v... | Wikipedia/Tree-based_models |
Applying machine learning (ML) (including deep learning) methods to the study of quantum systems is an emergent area of physics research. A basic example of this is quantum state tomography, where a quantum state is learned from measurement. Other examples include learning Hamiltonians, learning quantum phase transitio... | Wikipedia/Machine_learning_in_physics |
Sun Microsystems, Inc., often known as Sun for short, was an American technology company that existed from 1982 to 2010 which developed and sold computers, computer components, software, and information technology services. Sun contributed significantly to the evolution of several key computing technologies, among them... | Wikipedia/Sun_Microsystems |
In statistics and machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from any of the constituent learning algorithms alone.
Unlike a statistical ensemble in statistical mechanics, which is usually infinite, a machine learning ensemble consi... | Wikipedia/Ensemble_methods |
Portable Network Graphics (PNG, officially pronounced PING, colloquially pronounced PEE-en-JEE) is a raster-graphics file format that supports lossless data compression. PNG was developed as an improved, non-patented replacement for Graphics Interchange Format (GIF).
PNG supports palette-based images (with palettes o... | Wikipedia/Portable_Network_Graphics |
Neural Designer is a software tool for machine learning based on neural networks, a main area of artificial intelligence research, and contains a graphical user interface which simplifies data entry and interpretation of results.
In 2015, Neural Designer was chosen by the European Commission, within the Horizon 2020 pr... | Wikipedia/Neural_Designer |
A Hopfield network (or associative memory) is a form of recurrent neural network, or a spin glass system, that can serve as a content-addressable memory. The Hopfield network, named for John Hopfield, consists of a single layer of neurons, where each neuron is connected to every other neuron except itself. These connec... | Wikipedia/Hopfield_network |
The generalized Hebbian algorithm, also known in the literature as Sanger's rule, is a linear feedforward neural network for unsupervised learning with applications primarily in principal components analysis. First defined in 1989, it is similar to Oja's rule in its formulation and stability, except it can be applied t... | Wikipedia/Generalized_Hebbian_algorithm |
The Model Context Protocol (MCP) is an open standard, open-source framework introduced by Anthropic to standardize the way artificial intelligence (AI) models like large language models (LLMs) integrate and share data with external tools, systems, and data sources. Technology writers have dubbed MCP “the USB-C of AI ap... | Wikipedia/Model_Context_Protocol |
A chromosome or genotype in evolutionary algorithms (EA) is a set of parameters which define a proposed solution of the problem that the evolutionary algorithm is trying to solve. The set of all solutions, also called individuals according to the biological model, is known as the population. The genome of an individual... | Wikipedia/Chromosome_(evolutionary_algorithm) |
In computer networking, a heterogeneous network is a network connecting computers and other devices where the operating systems and protocols have significant differences. For example, local area networks (LANs) that connect Windows, Linux and Macintosh computers are heterogeneous.
Heterogeneous network also describes ... | Wikipedia/Heterogeneous_network |
Lateral movement refers to the techniques that cyber attackers, or threat actors, use to progressively move through a network as they search for the key data and assets that are ultimately the target of their attack campaigns. While the development of more sophisticated sequences of attack has helped threat actors deve... | Wikipedia/Network_Lateral_Movement |
In graph theory, the diameter of a connected undirected graph is the farthest distance between any two of its vertices. That is, it is the diameter of a set for the set of vertices of the graph, and for the shortest-path distance in the graph. Diameter may be considered either for weighted or for unweighted graphs. Res... | Wikipedia/Diameter_(graph_theory) |
A citation graph (or citation network), in information science and bibliometrics, is a directed graph that describes the citations within a collection of documents.
Each vertex (or node) in the graph represents a document in the collection, and each edge is directed from one document toward another that it cites (or vi... | Wikipedia/Citation_graph |
In graph theory, the Weisfeiler Leman graph isomorphism test is a heuristic test for the existence of an isomorphism between two graphs G and H. It is a generalization of the color refinement algorithm and has been first described by Weisfeiler and Leman in 1968. The original formulation is based on graph canonization,... | Wikipedia/Weisfeiler_Leman_graph_isomorphism_test |
In mathematics, a differentiable function of one real variable is a function whose derivative exists at each point in its domain. In other words, the graph of a differentiable function has a non-vertical tangent line at each interior point in its domain. A differentiable function is smooth (the function is locally well... | Wikipedia/Differentiable_functions |
A temporal network, also known as a time-varying network, is a network whose links are active only at certain points in time. Each link carries information on when it is active, along with other possible characteristics such as a weight. Time-varying networks are of particular relevance to spreading processes, like the... | Wikipedia/Temporal_network |
The nearest neighbor graph (NNG) is a directed graph defined for a set of points in a metric space, such as the Euclidean distance in the plane. The NNG has a vertex for each point, and a directed edge from p to q whenever q is a nearest neighbor of p, a point whose distance from p is minimum among all the given points... | Wikipedia/Nearest_neighbor_graph |
An industrial robot is a robot system used for manufacturing. Industrial robots are automated, programmable and capable of movement on three or more axes.
Typical applications of robots include welding, painting, assembly, disassembly, pick and place for printed circuit boards, packaging and labeling, palletizing, prod... | Wikipedia/Industrial_robot |
A remote-control vehicle, is defined as any vehicle that is teleoperated by a means that does not restrict its motion with an origin external to the device. This is often a radio-control device, a cable between the controller and the vehicle, or an infrared controller.
== Applications ==
=== Scientific ===
Remote-c... | Wikipedia/Remote-control_vehicle |
Visual servoing, also known as vision-based robot control and abbreviated VS, is a technique which uses feedback information extracted from a vision sensor (visual feedback) to control the motion of a robot. One of the earliest papers that talks about visual servoing was from the SRI International Labs in 1979.
== Vi... | Wikipedia/Vision_Based_Robot_Control |
A vision-guided robot (VGR) system is a robot fitted with one or more cameras used as sensors to provide a secondary feedback signal to the robot controller for a more accurate movement to a variable target position. VGR is rapidly transforming production processes by enabling robots to be highly adaptable and more eas... | Wikipedia/Vision-guided_robot_systems |
Boston Dynamics, Inc., is an American engineering and robotics design company founded in 1992 as a spin-off from the Massachusetts Institute of Technology. Headquartered in Waltham, Massachusetts, Boston Dynamics has been owned by the Hyundai Motor Group since December 2020, but it only completed the acquisition in Jun... | Wikipedia/Boston_Dynamics |
Evolutionary algorithms (EA) reproduce essential elements of the biological evolution in a computer algorithm in order to solve "difficult" problems, at least approximately, for which no exact or satisfactory solution methods are known. They belong to the class of metaheuristics and are a subset of population based bio... | Wikipedia/Evolutionary_methods |
Adaptive cruise control (ACC) is a type of advanced driver-assistance system for road vehicles that automatically adjusts the vehicle speed to maintain a safe distance from vehicles ahead. As of 2019, it is also called by 20 unique names that describe that basic functionality. This is also known as Dynamic cruise contr... | Wikipedia/Adaptive_cruise_control |
A Vehicular ad hoc network (VANET) is a proposed type of mobile ad hoc network (MANET) involving road vehicles. VANETs were first proposed in 2001 as "car-to-car ad-hoc mobile communication and networking" applications, where networks could be formed and information could be relayed among cars. It has been shown that ... | Wikipedia/Vehicular_ad_hoc_network |
Real-time Control System (RCS) is a reference model architecture, suitable for many software-intensive, real-time computing control problem domains. It defines the types of functions needed in a real-time intelligent control system, and how these functions relate to each other.
RCS is not a system design, nor is it a... | Wikipedia/Real-time_Control_System |
Mathematics of Control, Signals, and Systems is a peer-reviewed scientific journal that covers research concerned with mathematically rigorous system theoretic aspects of control and signal processing. The journal was founded by Eduardo Sontag and Bradley Dickinson in 1988. The editors-in-chief are Lars Gruene, Eduard... | Wikipedia/Mathematics_of_Control,_Signals,_and_Systems |
Artificial neural networks are a class of models used in machine learning, and inspired by biological neural networks. They are the core component of modern deep learning algorithms. Computation in artificial neural networks is usually organized into sequential layers of artificial neurons. The number of neurons in a l... | Wikipedia/Large_width_limits_of_neural_networks |
Nonparametric statistics is a type of statistical analysis that makes minimal assumptions about the underlying distribution of the data being studied. Often these models are infinite-dimensional, rather than finite dimensional, as in parametric statistics. Nonparametric statistics can be used for descriptive statistics... | Wikipedia/Non-parametric_methods |
There are many types of artificial neural networks (ANN).
Artificial neural networks are computational models inspired by biological neural networks, and are used to approximate functions that are generally unknown. Particularly, they are inspired by the behaviour of neurons and the electrical signals they convey betwe... | Wikipedia/Types_of_artificial_neural_networks |
Automated lane keeping systems (ALKS), also described as traffic jam chauffeurs, is an autonomous driving system that doesn't require driver supervision on motorways. ALKS is an international standard set out in UN-ECE regulation 157 and amounts to Level 3 vehicle automation. It is essentially a more robust combination... | Wikipedia/Automated_Lane_Keeping_Systems |
Neural network software is used to simulate, research, develop, and apply artificial neural networks, software concepts adapted from biological neural networks, and in some cases, a wider array of adaptive systems such as artificial intelligence and machine learning.
== Simulators ==
Neural network simulators are sof... | Wikipedia/Neural_network_software |
In general, a function approximation problem asks us to select a function among a well-defined class that closely matches ("approximates") a target function in a task-specific way. The need for function approximations arises in many branches of applied mathematics, and computer science in particular , such as predictin... | Wikipedia/Function_approximation |
Group method of data handling (GMDH) is a family of inductive, self-organizing algorithms for mathematical modelling that automatically determines the structure and parameters of models based on empirical data. GMDH iteratively generates and evaluates candidate models, often using polynomial functions, and selects the ... | Wikipedia/Group_method_of_data_handling |
The von Neumann architecture—also known as the von Neumann model or Princeton architecture—is a computer architecture based on the First Draft of a Report on the EDVAC, written by John von Neumann in 1945, describing designs discussed with John Mauchly and J. Presper Eckert at the University of Pennsylvania's Moore Sch... | Wikipedia/Von_Neumann_model |
An artificial neural network (ANN) combines biological principles with advanced statistics to solve problems in domains such as pattern recognition and game-play. ANNs adopt the basic model of neuron analogues connected to each other in a variety of ways.
== Structure ==
=== Neuron ===
A neuron with label
... | Wikipedia/Mathematics_of_artificial_neural_networks |
In the field of mathematical modeling, a radial basis function network is an artificial neural network that uses radial basis functions as activation functions. The output of the network is a linear combination of radial basis functions of the inputs and neuron parameters. Radial basis function networks have many uses,... | Wikipedia/Radial_basis_function_network |
The term hybrid neural network can have two meanings:
Biological neural networks interacting with artificial neuronal models, and
Artificial neural networks with a symbolic part (or, conversely, symbolic computations with a connectionist part).
As for the first meaning, the artificial neurons and synapses in hybrid n... | Wikipedia/Hybrid_neural_network |
The cerebellar model arithmetic computer (CMAC) is a type of neural network based on a model of the mammalian cerebellum. It is also known as the cerebellar model articulation controller. It is a type of associative memory.
The CMAC was first proposed as a function modeler for robotic controllers by James Albus in 1975... | Wikipedia/Cerebellar_model_articulation_controller |
Time delay neural network (TDNN) is a multilayer artificial neural network architecture whose purpose is to 1) classify patterns with shift-invariance, and 2) model context at each layer of the network. It is essentially a 1-d convolutional neural network (CNN).
Shift-invariant classification means that the classifier ... | Wikipedia/Time_delay_neural_network |
In the mathematical theory of artificial neural networks, universal approximation theorems are theorems of the following form: Given a family of neural networks, for each function
f
{\displaystyle f}
from a certain function space, there exists a sequence of neural networks
... | Wikipedia/Universal_approximation_theorem |
In computer strategy games, for example in shogi and chess, an efficiently updatable neural network (NNUE, a Japanese wordplay on Nue, sometimes stylised as ƎUИИ) is a neural network-based evaluation function whose inputs are piece-square tables, or variants thereof like the king-piece-square table. NNUE is used primar... | Wikipedia/Efficiently_updatable_neural_network |
The softmax function, also known as softargmax: 184 or normalized exponential function,: 198 converts a tuple of K real numbers into a probability distribution of K possible outcomes. It is a generalization of the logistic function to multiple dimensions, and is used in multinomial logistic regression. The softmax fu... | Wikipedia/Softmax_activation_function |
In machine learning and statistics, the learning rate is a tuning parameter in an optimization algorithm that determines the step size at each iteration while moving toward a minimum of a loss function. Since it influences to what extent newly acquired information overrides old information, it metaphorically represents... | Wikipedia/Adaptive_learning_rate |
The wake-sleep algorithm is an unsupervised learning algorithm for deep generative models, especially Helmholtz Machines. The algorithm is similar to the expectation-maximization algorithm, and optimizes the model likelihood for observed data. The name of the algorithm derives from its use of two learning phases, the “... | Wikipedia/Wake-sleep_algorithm |
Context-aware computing refers to a general class of mobile systems that can sense their physical environment, and adapt their behavior accordingly.
Three important aspects of context are: where you are; who you are with; and what resources are nearby. Although location is a primary capability, location-aware does not ... | Wikipedia/Context-aware_pervasive_systems |
Fitness approximation aims to approximate the objective or fitness functions in evolutionary optimization by building up machine learning models based on data collected from numerical simulations or physical experiments. The machine learning models for fitness approximation are also known as meta-models or surrogates, ... | Wikipedia/Fitness_approximation |
YouTube Rewind 2018: Everyone Controls Rewind (also known as YouTube Rewind 2018) is a video that was uploaded to the official channel of the video-sharing website YouTube on December 6, 2018, as the ninth installment of the YouTube Rewind series. The video features references to video games and internet culture, starr... | Wikipedia/YouTube_Rewind_2018:_Everyone_Controls_Rewind |
The Google Knowledge Graph is a knowledge base from which Google serves relevant information in an infobox beside its search results. This allows the user to see the answer in a glance, as an instant answer. The data is generated automatically from a variety of sources, covering places, people, businesses, and more.
Th... | Wikipedia/Google_Knowledge_Graph |
Piper is a centralized version control system used by Google for its internal software development. Originally designed for Linux, it supports Microsoft Windows and macOS since October 2012.
== Scale ==
Since its founding years Google used a central codebase shared by the developers. For over 10 years Google relied o... | Wikipedia/Piper_(source_control_system) |
Federated Learning of Cohorts (FLoC) is a type of web tracking. It groups people into "cohorts" based on their browsing history for the purpose of interest-based advertising. FLoC was being developed as a part of Google's Privacy Sandbox initiative, which includes several other advertising-related technologies with bir... | Wikipedia/Federated_Learning_of_Cohorts |
Global IP Solutions (also known as GIPS) was a United States–based corporation that developed real-time voice and video processing software for IP networks, before it was acquired by Google in May 2010. The company delivered embedded software that enabled real-time communications capabilities for video and voice over I... | Wikipedia/Global_IP_Solutions |
The Skia Graphics Engine or Skia is an open-source 2D graphics library written in C++. Skia abstracts away platform-specific graphics APIs (which differ from one to another). Skia Inc. originally developed the library; Google acquired it in 2005, and then released the software as open source licensed under the New BSD ... | Wikipedia/Skia_Graphics_Engine |
Google Energy LLC is a subsidiary company of Alphabet Inc., which was created to reduce costs of energy consumption of the Google Group, and subsequently to produce and sell clean energy. The division also allows it to take advantage of projects funded through the philanthropic Google.org.
== Operations ==
By 2007 G... | Wikipedia/Google_Energy |
Bump was an iOS and Android mobile app that enabled smartphone users to transfer contact information, photos and files between devices. In 2011, it was #8 on Apple's list of all-time most popular free iPhone apps, and by February 2013 it had been downloaded 125 million times. Its developer, Bump Technologies, shut down... | Wikipedia/Bump_(application) |
Google Tensor is a series of ARM64-based system-on-chip (SoC) processors designed by Google for its Pixel devices. It was originally conceptualized in 2016, following the introduction of the first Pixel smartphone, though actual developmental work did not enter full swing until 2020. The first-generation Tensor chip de... | Wikipedia/Google_Tensor |
The Google Science Fair was a worldwide (excluding Cuba, Iran, North Korea, Sudan, Myanmar/Burma, Syria, Zimbabwe and any other U.S. sanctioned country) online science competition sponsored by Google, Lego, Virgin Galactic, National Geographic and Scientific American. It was an annual event from 2011 to 2018.
The first... | Wikipedia/Google_Science_Fair |
The Google Affiliate Network was the affiliate marketing company, specifically affiliate network, formerly known as Doubleclick Performics, which was bought by Google in 2007. On April 16, 2013, Google announced the closure of the Google Affiliate Network.
== History ==
DoubleClick announced the acquisition of Double... | Wikipedia/Google_Affiliate_Network |
Marratech was a Swedish company that made software for e-meetings (e.g., web conferencing, videoconferencing). It was acquired by Google in 2007.
== History ==
Marratech was founded in 1998, as a spin-off company from the Centre for Distance-Spanning Technology at the Luleå University of Technology. Founders include ... | Wikipedia/Marratech |
Google Pay (formerly Android Pay) is a mobile payment service developed by Google to power in-app, online, and in-person contactless purchases on mobile devices, enabling users to make payments with Android phones, tablets, or watches. Users can authenticate via a PIN, passcode, or biometrics such as 3D face scanning o... | Wikipedia/Google_Pay_(payment_method) |
Internet Low Bitrate Codec (iLBC) is a royalty-free narrowband speech audio coding format and an open-source reference implementation (codec), developed by Global IP Solutions (GIPS) formerly Global IP Sound (acquired by Google Inc in 2011). It was formerly freeware with limitations on commercial use, but since 2011 it... | Wikipedia/Internet_Low_Bitrate_Codec |
In May 2013, the German Federal Court of Justice stated that Google's predictions within the autocomplete function of its web search engine can violate the right of personality. The right of personality ensures that a person's (or even a company's) personality (reputation) is respected and can be freely developed. Only... | Wikipedia/Judgement_of_the_German_Federal_Court_of_Justice_on_Google's_autocomplete_function |
Google Web Designer is a drag-and-drop page builder for Windows, macOS, and Linux from Google for creating interactive HTML5 ads and other HTML5 content. It offers a GUI with common design tools, such as a “Text” tool that integrates with Google Web Fonts, a “Shapes” tool, a “Pen” tool, and 3D tools. The advertising fe... | Wikipedia/Google_Web_Designer |
AMP (originally an acronym for Accelerated Mobile Pages) is an open source HTML framework developed by the AMP Open Source Project. It was originally created by Google as a competitor to Facebook Instant Articles and Apple News. AMP is optimized for mobile web browsing and intended to help webpages load faster. AMP pag... | Wikipedia/Accelerated_Mobile_Pages |
Material Design (codename Quantum Paper) is a design language developed by Google in 2014. Expanding on the "cards" UI that debuted in Google Now, Material Design uses more grid-based layouts, responsive animations and transitions, padding, and depth effects such as lighting and shadows. Google announced the initial ve... | Wikipedia/Material_Design |
XLA (Accelerated Linear Algebra) is an open-source compiler for machine learning developed by the OpenXLA project. XLA is designed to improve the performance of machine learning models by optimizing the computation graphs at a lower level, making it particularly useful for large-scale computations and high-performance ... | Wikipedia/Accelerated_Linear_Algebra |
In statistics, a tobit model is any of a class of regression models in which the observed range of the dependent variable is censored in some way. The term was coined by Arthur Goldberger in reference to James Tobin, who developed the model in 1958 to mitigate the problem of zero-inflated data for observations of house... | Wikipedia/Tobit_model |
The swish function is a family of mathematical function defined as follows:
swish
β
(
x
)
=
x
sigmoid
(
β
x
)
=
... | Wikipedia/Swish_(function) |
In mathematics, an algebraic function is a function that can be defined
as the root of an irreducible polynomial equation. Algebraic functions are often algebraic expressions using a finite number of terms, involving only the algebraic operations addition, subtraction, multiplication, division, and raising to a fracti... | Wikipedia/Algebraic_functions |
The swish function is a family of mathematical function defined as follows:
swish
β
(
x
)
=
x
sigmoid
(
β
x
)
=
... | Wikipedia/Swish_function |
In mathematics, the Johnson–Lindenstrauss lemma is a result named after William B. Johnson and Joram Lindenstrauss concerning low-distortion embeddings of points from high-dimensional into low-dimensional Euclidean space. The lemma states that a set of points in a high-dimensional space can be embedded into a space of ... | Wikipedia/Johnson–Lindenstrauss_lemma |
In applied mathematics, Gabor atoms, or Gabor functions, are functions used in the analysis proposed by Dennis Gabor in 1946 in which a family of functions is built from translations and modulations of a generating function.
== Overview ==
In 1946, Dennis Gabor suggested the idea of using a granular system to produce... | Wikipedia/Gabor_function |
In artificial intelligence (AI), a foundation model (FM), also known as large X model (LxM), is a machine learning or deep learning model trained on vast datasets so that it can be applied across a wide range of use cases. Generative AI applications like large language models (LLM) are common examples of foundation mod... | Wikipedia/Vision-language_model |
A large language model (LLM) is a machine learning model designed for natural language processing tasks, especially language generation. LLMs are language models with many parameters, and are trained with self-supervised learning on a vast amount of text.
The largest and most capable LLMs are generative pretrained tran... | Wikipedia/Large_language_models |
The Rasch model, named after Georg Rasch, is a psychometric model for analyzing categorical data, such as answers to questions on a reading assessment or questionnaire responses, as a function of the trade-off between the respondent's abilities, attitudes, or personality traits, and the item difficulty. For example, th... | Wikipedia/Rasch_model |
The MM algorithm is an iterative optimization method which exploits the convexity of a function in order to find its maxima or minima. The MM stands for “Majorize-Minimization” or “Minorize-Maximization”, depending on whether the desired optimization is a minimization or a maximization. Despite the name, MM itself is n... | Wikipedia/MM_algorithm |
For parsing algorithms in computer science, the inside–outside algorithm is a way of re-estimating production probabilities in a probabilistic context-free grammar. It was introduced by James K. Baker in 1979 as a generalization of the forward–backward algorithm for parameter estimation on hidden Markov models to stoch... | Wikipedia/Inside-outside_algorithm |
ELKI (Environment for Developing KDD-Applications Supported by Index-Structures) is a data mining (KDD, knowledge discovery in databases) software framework developed for use in research and teaching. It was originally created by the database systems research unit at the Ludwig Maximilian University of Munich, Germany,... | Wikipedia/Environment_for_DeveLoping_KDD-Applications_Supported_by_Index-Structures |
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