Tree of Thoughts
Definition
Tree of Thoughts (ToT) extends traditional chain-of-thought prompting by allowing the …
Algorithms
Quantum machine learning
Definition
Quantum machine learning (QML) is an emerging interdisciplinary field that integrates …
Object Detection
Definition
Object detection extends image classification by not only determining what objects are …
Maximum inner-product search
Definition
Maximum Inner-Product Search (MIPS) is a fundamental problem in information retrieval and …
Lifelong Planning A*
Definition
Lifelong Planning A* (LPA*) is an extension of the A* search algorithm designed for …
Lazy learning
Definition
Lazy learners, such as k-Nearest Neighbors (k-NN), memorize the entire training dataset …
Hierarchical navigable small world
Definition
The Hierarchical Navigable Small World (HNSW) algorithm constructs a multi-layered graph …
Extremal optimization
Definition
Unlike genetic algorithms that maintain a population, EO works on a single solution. It …
Discovery System
Definition
A discovery system is a computational framework aimed at accelerating scientific or …
Differentially private stochastic gradient descent
Definition
DP-SGD is a variant of Stochastic Gradient Descent designed to protect the privacy of …
Cross-entropy method
Definition
The Cross-Entropy Method (CEM) is a powerful general-purpose optimization algorithm used …
Computational heuristic intelligence
Definition
Computational heuristic intelligence involves algorithms that employ rules of thumb, …
Ball tree
Definition
A Ball tree partitions data points into nested hyperspheres (balls) rather than …
Automated negotiation
Definition
Automated negotiation involves software agents that represent human interests in …
Actor-critic algorithm
Definition
The actor-critic algorithm employs two components: the actor, which updates the policy to …
Unsupervised Learning
Definition
Unsupervised learning identifies hidden structures, clusters, or distributions within raw …
Optimization
Definition
In machine learning, optimization refers to the algorithms used to adjust model …
one-step
Definition
In machine learning and optimization, one-step methods solve problems directly without …
on-policy
Definition
On-policy algorithms require that the agent learns directly from the actions taken by its …
Reinforcement Learning
Definition
Reinforcement Learning (RL) is a branch of machine learning focused on how intelligent …
Search
Definition
Search is a fundamental paradigm in AI used to navigate complex problem spaces, such as …
Matching
Definition
Matching is a critical technique in machine learning used to establish relationships …
Decision
Definition
Decision-making in AI involves selecting the optimal action from a set of possibilities …
Carlo
Definition
Monte Carlo methods are essential techniques in AI and statistics for approximating …
Adam
Definition
Adam (Adaptive Moment Estimation) is a popular first-order gradient-based optimization …
Backpropagation
Definition
Backpropagation, short for backward propagation of errors, is a method used in artificial …