Algorithms
37 AI Wiki articles on Algorithms. The most referenced are Simultaneous Localization and Mapping (SLAM), XGBoost and LightGBM.
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A*
A\ (pronounced "A-star") is a best-first graph search algorithm that finds a least-cost path from a start node to a goal node. It evaluates candidate paths...
Artificial Intelligence
Actor-critic methods
Actor-critic methods are a family of reinforcement learning algorithms that learn two things at once: a parameterized policy, called the actor, which chooses...
Deep LearningMachine Learning
AlphaDev
AlphaDev is an artificial intelligence system built by Google DeepMind that used deep reinforcement learning to discover faster algorithms for common computing...
Google DeepMindReinforcement Learning
BM25 (Okapi BM25)
BM25, also called Okapi BM25 or Best Match 25, is a probabilistic ranking function used by search engines and information retrieval systems to estimate how...
Information Retrieval
CART algorithm
The CART algorithm (Classification And Regression Trees) is a non-parametric supervised learning method that builds a binary decision tree from labelled...
Machine Learning
CatBoost
CatBoost is an open-source gradient boosted decision trees library developed by Yandex and released to the public on July 18, 2017 [1][5]. The name is a...
Machine LearningOpen Source AI
Conditional Random Field
A conditional random field (CRF) is a discriminative probabilistic model for structured prediction, used most often to assign a label to every position in an...
Machine LearningNatural Language Processing
Dynamic Programming
Dynamic programming (DP) is an algorithmic technique that solves a complex problem by breaking it into simpler overlapping subproblems, solving each subproblem...
Artificial IntelligenceMachine Learning
Feature Selection
Feature selection is the process of choosing a subset of the most relevant input variables (features) from a larger candidate pool for use in a machine...
Data & DatasetsMachine Learning
Flash Attention 3
Flash Attention 3 (FA3, styled FlashAttention-3) is the third generation of the FlashAttention algorithm, an exact-attention GPU kernel designed to exploit...
AI HardwareTransformer Models
Flash-Decoding
Flash-Decoding is an inference-time variant of the FlashAttention algorithm that targets the decoding (autoregressive generation) phase of large language model...
AI Inference
HNSW
Hierarchical Navigable Small World (HNSW) is an approximate nearest-neighbor search algorithm that indexes high-dimensional vectors in a multi-layer proximity...
Information RetrievalMachine Learning
Kalman Filter
The Kalman filter is a recursive algorithm that estimates the hidden state of a dynamic system from a sequence of noisy measurements. Rudolf E. Kalman...
Machine LearningRobotics
LightGBM
LightGBM (short for Light Gradient-Boosting Machine) is a free and open-source gradient boosting framework that trains ensembles of decision trees on tabular...
Machine LearningOpen Source AI
Lion (optimizer)
Lion (EvoLved Sign Momentum) is a stochastic optimizer for training deep neural networks, introduced by researchers at Google in the February 2023 paper...
GoogleTraining & Optimization
Lookahead Decoding
Lookahead Decoding is a parallel decoding algorithm for accelerating inference in large language models, introduced in November 2023 by Yichao Fu, Peter...
AI InferenceLarge Language Models
Markov Chain Monte Carlo
Markov Chain Monte Carlo (MCMC) is a class of algorithms for drawing samples from a probability distribution by constructing a Markov chain whose stationary...
Statistics
Matrix multiplication
Matrix multiplication combines an M by K matrix A with a K by N matrix B to produce an M by N matrix C, in which every entry of C is the dot product of one row...
AI HardwareDeep Learning
Monte Carlo Tree Search
Monte Carlo Tree Search (MCTS) is a heuristic search algorithm for sequential decision-making that finds strong actions by running many simulated playthroughs...
AI in GamingReinforcement Learning
Motion planning
Motion planning is the computational problem of finding a sequence of valid configurations or controls that moves a robot (or another articulated or dynamical...
Robotics
Multi-armed bandit
A multi-armed bandit is a sequential decision problem in which a learner repeatedly picks one action from a fixed set, receives a random reward for that action...
Machine LearningReinforcement Learning
Nash equilibrium
A Nash equilibrium is a combination of strategies, one for each player in a game, such that no player can raise their own payoff by changing strategy alone...
Computer ScienceMathematics
Particle Filter
A particle filter is a simulation-based method for estimating the changing, unobserved state of a system from a sequence of noisy observations. It represents a...
Machine LearningRobotics
Probabilistic Graphical Model
A probabilistic graphical model (PGM) is a mathematical representation in which a graph expresses the factorization and conditional-independence structure of a...
Machine LearningStatistics
Quantum computing
Quantum computing is a model of computation that stores and manipulates information in quantum mechanical systems, using superposition, entanglement, and...
AI HardwareAI for Science
SMOTE (Synthetic Minority Over-sampling Technique)
SMOTE (Synthetic Minority Over-sampling Technique) is a data preprocessing algorithm that fixes class imbalance by creating new synthetic minority-class...
Machine Learning
Shapley value
The Shapley value is a rule from cooperative game theory for dividing the payoff of a group among its members. Given a set of players and a function stating...
InterpretabilityMachine Learning
Simulated annealing
Simulated annealing is a probabilistic method for finding a good approximate solution to a global optimization problem, especially one with many local optima...
Machine LearningStatistics
Simultaneous Localization and Mapping (SLAM)
Simultaneous Localization and Mapping (SLAM) is the computational problem of building a map of an unknown environment while at the same time estimating the...
Computer VisionRobotics
Sketching
See also: Machine learning terms Sketching is a family of techniques in computer science, machine learning, and database systems that use small probabilistic...
Computer Science
Soft Actor-Critic
Soft Actor-Critic (SAC) is an off-policy, maximum-entropy deep reinforcement learning algorithm that trains a stochastic actor-critic to maximize expected...
Deep LearningReinforcement Learning
TF-IDF (Term Frequency-Inverse Document Frequency)
TF-IDF (term frequency-inverse document frequency) is a numerical statistic that measures how important a word is to a single document within a larger...
Information RetrievalNatural Language Processing
Temporal-difference learning
Temporal-difference (TD) learning is a class of model-free reinforcement learning methods that learn value-function estimates by bootstrapping: updating each...
Machine LearningReinforcement Learning
Top-k sampling
Top-k sampling is a decoding strategy for autoregressive language models that restricts each generation step to the k most probable next tokens. At every...
AI InferenceLarge Language Models
Twin Delayed DDPG
Twin Delayed Deep Deterministic Policy Gradient (TD3) is an off-policy actor-critic reinforcement learning algorithm for continuous action spaces, introduced...
Deep LearningReinforcement Learning
XGBoost
See also: Gradient boosted (decision) trees, Gradient Boosting, LightGBM, CatBoost XGBoost (short for eXtreme Gradient Boosting) is an open-source software...
Machine LearningOpen Source AI
k-Nearest Neighbors
k-Nearest Neighbors (often abbreviated k-NN or KNN) is a non-parametric, instance-based supervised learning algorithm that classifies a new data point by...
Machine Learning