Tanh
Definition
The hyperbolic tangent (Tanh) function is a non-linear activation function commonly used …
Mathematics
Statistical learning theory
Definition
Statistical learning theory (SLT) is a branch of statistics and computer science that …
Solomonoff's theory of inductive inference
Definition
Developed by Ray Solomonoff, this theory provides a universal model of induction by …
Sigmoid
Definition
The sigmoid function, defined as σ(z) = 1 / (1 + e^-z), is widely used in machine …
Proximal gradient methods for learning
Definition
Proximal gradient methods are iterative optimization techniques used when the loss …
Pattern theory
Definition
Pattern theory provides a rigorous mathematical foundation for understanding how complex …
Normalization
Definition
Common methods include Min-Max scaling and Z-score standardization. This process ensures …
Linear predictor function
Definition
In statistical modeling and machine learning, a linear predictor function represents the …
Isotropic position
Definition
In convex geometry and high-dimensional probability, a set of points or a convex body is …
Gabbay's separation theorem
Definition
Gabbay’s separation theorem is a fundamental concept in mathematical logic, …
Game theory
Definition
Game theory is a branch of applied mathematics that models strategic interactions between …
FrontierMath
Definition
FrontierMath is a specialized evaluation suite created to test the limits of large …
Formal concept analysis
Definition
FCA provides a rigorous framework for analyzing relationships between objects and their …
Differential Privacy
Definition
Differential privacy provides strong privacy guarantees by adding calibrated statistical …
Curse of dimensionality
Definition
The curse of dimensionality refers to various phenomena that arise when analyzing data in …
CHAOS
Definition
Chaos theory explores how small variations in starting parameters can lead to vastly …
Automated Mathematician
Definition
An Automated Mathematician utilizes machine learning and symbolic reasoning to explore …
AIXI
Definition
AIXI is a theoretical framework proposed by Marcus Hutter that defines an idealized …
Vector
Definition
In artificial intelligence, a vector is a fundamental data structure used to represent …
Optimization
Definition
In machine learning, optimization refers to the algorithms used to adjust model …
Loss Function
Definition
Also known as the cost or error function, the loss function provides a scalar value …
Gradient Descent
Definition
Gradient descent is a first-order iterative optimization algorithm for finding a local …
Activation Function
Definition
An activation function introduces non-linearity into a neural network, allowing it to …
Random
Definition
Randomness is fundamental in AI for initializing model weights, shuffling datasets, and …
Point
Definition
A point in AI contexts usually denotes a discrete coordinate within a feature space or …
Numerical
Definition
In the context of AI and data science, numerical refers to data types or methods that …
Latent
Definition
In machine learning, latent variables are unobserved factors that influence observed …
Linear
Definition
Linear operations involve multiplication and addition without non-linear activations. In …
Langevin
Definition
Langevin dynamics incorporates random noise and damping forces to explore energy …
Group
Definition
In mathematics and theoretical computer science, a group is a set G together with a …