User:Zarzuelazen/Books/Reality Theory: Machine Learning

From Wikipedia, the free encyclopedia
Jump to navigation Jump to search

This user book is a user-generated collection of Wikipedia articles that can be easily saved, rendered electronically, and ordered as a printed book. If you are the creator of this book and need help, see Help:Books (general tips) and WikiProject Wikipedia-Books (questions and assistance).

Edit this book: Book Creator · Wikitext
Order a printed copy from: PediaPress
About ] [ Advanced ] [ FAQ ] [ Feedback ] [ Help ] [ WikiProject ] Recent Changes ]

Reality Theory: Machine Learning[edit]

3D pose estimation
Acoustic model
Activation function
Active contour model
Active learning (machine learning)
Activity recognition
Adaptive resonance theory
Adversarial machine learning
Affine shape adaptation
Algorithm selection
Ancestral graph
Anomaly detection
Artificial neural network
Artificial neuron
Association rule learning
Autoassociative memory
Automated machine learning
Automatic summarization
Bag-of-words model in computer vision
Baillie–PSW primality test
Barabási–Albert model
Batch normalization
Baum–Welch algorithm
Bayesian hierarchical modeling
Bayesian multivariate linear regression
Bayesian network
Belief propagation
Betweenness centrality
Bias–variance tradeoff
Bidirectional associative memory
Bidirectional recurrent neural networks
Binary classification
Blob detection
Boltzmann machine
Boosting (machine learning)
Bootstrap aggregating
C4.5 algorithm
Caffe (software)
Camera matrix
Canonical correlation
Capsule neural network
Catastrophic interference
Cerebellar model articulation controller
Cluster analysis
Cluster hypothesis
Cluster labeling
Collaborative filtering
Community search
Community structure
Competitive learning
Complex network
Computational learning theory
Computational statistics
Computer stereo vision
Computer vision
Computing the permanent
Concept search
Conceptual clustering
Conditional random field
Confirmatory factor analysis
Confusion matrix
Connected-component labeling
Constellation model
Constrained conditional model
Content discovery platform
Content-based image retrieval
Convolutional neural network
Corner detection
Correspondence analysis
Correspondence problem
Cosine similarity
Cross-validation (statistics)
Curse of dimensionality
Curve fitting
Data mining
Data pre-processing
Davies–Bouldin index
Decision boundary
Decision tree
Decision tree learning
Deep belief network
Deep learning
Degree distribution
Delta rule
Deming regression
Differentiable neural computer
Diffusion map
Dimensionality reduction
Discriminant function analysis
Discriminative model
Distribution learning theory
Divided differences
Document classification
Document clustering
Document retrieval
Domain adaptation
Dunn index
Dynamic Bayesian network
Dynamic time warping
Eager learning
Early stopping
Echo state network
Edge detection
Efficiency (network science)
Eigenvalue algorithm
Elastic map
Email filtering
Empirical risk minimization
Ensemble averaging (machine learning)
Ensemble learning
Erdős–Rényi model
Error tolerance (PAC learning)
Essential matrix
Euclidean algorithm
Evaluation measures (information retrieval)
Evolving networks
Example-based machine translation
Expectation–maximization algorithm
Exploratory factor analysis
Exponential random graph models
Face detection
Facial recognition system
Factor analysis
Factor graph
Feature (computer vision)
Feature (machine learning)
Feature detection (computer vision)
Feature engineering
Feature extraction
Feature hashing
Feature learning
Feature scaling
Feature selection
Feature vector
Feedforward neural network
Fermat primality test
Fixed effects model
Forward algorithm
Forward–backward algorithm
Function approximation
Fundamental matrix (computer vision)
Fusion adaptive resonance theory
Fuzzy clustering
Gated recurrent unit
Gaussian elimination
General linear model
Generalised Hough transform
Generalization error
Generalized linear model
Generative adversarial networks
Generative model
Gesture recognition
Gibbs sampling
Google Search
Gradient boosting
Graphical model
Grid method multiplication
Group method of data handling
Growth function
Handwriting recognition
Harris chain
Hermite interpolation
Hidden Markov model
Hierarchical clustering
Hierarchical clustering of networks
Hierarchical Deep Learning
Hierarchical hidden Markov model
Hierarchical network model
Hierarchical temporal memory
Histogram of oriented gradients
HITS algorithm
Hopfield network
Hough transform
Hyperbolic geometric graph
Hyperparameter (machine learning)
Hyperparameter optimization
ID3 algorithm
Image segmentation
Importance sampling
Incremental learning
Inductive bias
Influence diagram
Information extraction
Information filtering system
Information retrieval
Information visualization
Instance selection
Instantaneously trained neural networks
Interest point detection
Interval predictor model
Inverse iteration
Junction tree algorithm
K-means clustering
K-medians clustering
K-nearest neighbors algorithm
Karatsuba algorithm
Kernel density estimation
Kernel embedding of distributions
Kernel method
Kernel perceptron
Kernel principal component analysis
Lancichinetti–Fortunato–Radicchi benchmark
Language model
Lasso (statistics)
Latent class model
Latent growth modeling
Latent variable model
Lattice multiplication
Lazy learning
Learning curve (machine learning)
Learning rate
Learning to rank
Learning vector quantization
Least squares
Least-angle regression
Linear classifier
Linear discriminant analysis
Linear interpolation
Linear regression
Linear separability
Link analysis
Liquid state machine
List of datasets for machine learning research
Local regression
Local search (Internet)
Local tangent space alignment
Logistic regression
Long division
Long short-term memory
Loss function
Low-rank approximation
LU decomposition
Machine learning
Machine translation
Manifold alignment
Manifold regularization
Markov blanket
Markov chain
Markov chain Monte Carlo
Markov model
Markov random field
Matrix multiplication algorithm
Maximum-entropy Markov model
Mean field particle methods
Mean shift
Meta learning (computer science)
Metasearch engine
Method of moments (statistics)
Metropolis–Hastings algorithm
Miller–Rabin primality test
Mixed logit
Mixed model
Mixture model
MNIST database
Modular neural network
Modularity (networks)
Monte Carlo method
Motion estimation
Multi-label classification
Multi-task learning
Multiclass classification
Multidimensional scaling
Multilayer perceptron
Multilevel model
Multilinear principal component analysis
Multilinear subspace learning
Multinomial logistic regression
Multinomial probit
Multivariate adaptive regression spline
Naive Bayes classifier
Naive Bayes spam filtering
Negative search
Network controllability
Network science
Network theory
Neural architecture search
Neural Turing machine
Newton polynomial
Non-linear least squares
Non-negative matrix factorization
Nonlinear dimensionality reduction
Nonlinear regression
Nonparametric regression
Numerical linear algebra
Object Co-segmentation
Object detection
Occam learning
One-shot learning
Online machine learning
Optical character recognition
Optical flow
OPTICS algorithm
Ordered logit
Ordered probit
Ordinal regression
Ordinary least squares
Outline of object recognition
Part-based models
Partial least squares path modeling
Partial least squares regression
Path analysis (statistics)
Path coefficient
Pattern recognition
Pinhole camera model
Platt scaling
Point distribution model
Point set registration
Poisson regression
Polynomial interpolation
Polynomial regression
Pose (computer vision)
Power iteration
Precision and recall
Predictive analytics
Predictive modelling
Preference learning
Principal component analysis
Prior knowledge for pattern recognition
Probabilistic neural network
Probabilistic programming
Probably approximately correct learning
Probit model
Proximity search (text)
Pruning (decision trees)
QR algorithm
QR decomposition
Quantile regression
Quantum machine learning
Quantum neural network
Query expansion
Query understanding
Question answering
Rademacher complexity
Radial basis function
Radial basis function kernel
Radial basis function network
Random effects model
Random forest
Random sample consensus
Random subspace method
Randomized Hough transform
Ranking (information retrieval)
Receiver operating characteristic
Reciprocity (network science)
Recommender system
Rectifier (neural networks)
Recurrent neural network
Recursive neural network
Recursive partitioning
Regression analysis
Regularization (mathematics)
Relation network
Relevance (information retrieval)
Relevance vector machine
Representer theorem
Reservoir computing
Residual neural network
Restricted Boltzmann machine
Ridge detection
Root-mean-square deviation
Rubin causal model
Rule-based machine learning
Sample complexity
Scale space
Scale space implementation
Scale-free network
Scale-invariant feature transform
Scale-space axioms
Scale-space segmentation
Search aggregator
Search engine indexing
Search engine results page
Segmentation-based object categorization
Selection-based search
Self-organizing map
Semi-supervised learning
Semidefinite embedding
Sequence labeling
Sequential pattern mining
Shape context
Shattered set
Short division
Sieve of Atkin
Sieve of Eratosthenes
Sigmoid function
Similarity learning
Similarity measure
Simple linear regression
Small-world network
Softmax function
Solomonoff's theory of inductive inference
Solovay–Strassen primality test
Sparse dictionary learning
Sparse distributed memory
Sparse matrix
Sparse network
Spectral clustering
Speech processing
Speech recognition
Speech synthesis
Spiking neural network
Spline interpolation
Stability (learning theory)
Statistical classification
Statistical learning theory
Statistical machine translation
Stochastic block model
Structural equation modeling
Structural risk minimization
Structure mining
Structure tensor
Structured prediction
Structured support vector machine
Supervised learning
Support vector machine
T-distributed stochastic neighbor embedding
Temporal information retrieval
Text mining
Thresholding (image processing)
Tikhonov regularization
Time delay neural network
Topological data analysis
Total least squares
Training, test, and validation sets
Transduction (machine learning)
Transfer learning
Transformer (machine learning model)
Trial division
Triangulation (computer vision)
Types of artificial neural networks
Universal approximation theorem
Unsupervised learning
Vanishing gradient problem
Vapnik–Chervonenkis theory
Variable-order Markov model
Variance reduction
Variational Bayesian methods
VC dimension
Vector quantization
Video content analysis
Video tracking
Visual descriptor
Visual odometry
Viterbi algorithm
Wake-sleep algorithm
Watts–Strogatz model
Weak supervision
Web query classification
Web search engine
Web search query
Wheel factorization
Winnow (algorithm)