Toy problem
Definition
In artificial intelligence and computer science, a toy problem is a highly simplified …
Theory
The Master Algorithm
Definition
Coined by Pedro Domingos in his book of the same name, the ‘Master Algorithm’ …
Statistical learning theory
Definition
Statistical learning theory (SLT) is a branch of statistics and computer science that …
Structural risk minimization
Definition
Structural risk minimization (SRM) is a method for minimizing expected risk by …
Stability
Definition
In machine learning, stability refers to the robustness of a model’s performance …
Solomonoff's theory of inductive inference
Definition
Developed by Ray Solomonoff, this theory provides a universal model of induction by …
Sample complexity
Definition
In computational learning theory, sample complexity quantifies the amount of data needed …
Recursive self-improvement
Definition
Recursive self-improvement refers to the theoretical capability of an artificial …
Rademacher complexity
Definition
Rademacher complexity evaluates how well a hypothesis class can correlate with random …
Principle of rationality
Definition
This principle posits that an agent’s actions should be chosen to maximize its …
Pattern theory
Definition
Pattern theory provides a rigorous mathematical foundation for understanding how complex …
Parity Learning
Definition
Parity Learning is a benchmark problem in machine learning theory where the goal is to …
Neural modeling fields
Definition
Neural modeling fields involve the study of how neural populations organize themselves in …
Math
Definition
In the context of artificial intelligence, mathematics provides the theoretical framework …
Manifold hypothesis
Definition
This hypothesis explains why deep learning works effectively despite the curse of …
M-theory
Definition
While primarily a concept in theoretical physics rather than computer science, M-theory …
Lottery ticket hypothesis
Definition
The Lottery Ticket Hypothesis suggests that within a large, randomly initialized neural …
Linear separability
Definition
Linear separability refers to the geometric condition in which data points belonging to …
Learnable function class
Definition
In statistical learning theory, a learnable function class represents the hypothesis …
Language/action perspective
Definition
Rooted in speech act theory and pragmatics, this perspective emphasizes how utterances …
Isotropic position
Definition
In convex geometry and high-dimensional probability, a set of points or a convex body is …
Kernel embedding of distributions
Definition
Kernel Embedding of Distributions allows probabilistic objects to be treated as points in …
Inductive Bias
Definition
Inductive bias represents the inherent preferences or constraints built into a machine …
Inferential theory of learning
Definition
This theory posits that learning is essentially a process of probabilistic inference. …
Ideonomy
Definition
This field studies the processes behind how ideas are formed, combined, and evolved. It …
Gödel machine
Definition
The Gödel machine is a hypothetical universal problem solver proposed by Jürgen …
Grokking
Definition
Grokking refers to a counter-intuitive behavior observed in deep learning where a model …
Grammar systems theory
Definition
Originating from theoretical computer science and linguistics, this field extends …
Granular computing
Definition
This approach mimics human cognitive processes by grouping data into higher-level …
Gabbay's separation theorem
Definition
Gabbay’s separation theorem is a fundamental concept in mathematical logic, …
Fon
Definition
In the context of AI terminology, ‘Fon’ is often used to describe the core …
Evolvability
Definition
In computational contexts, evolvability refers to how easily an algorithm or neural …
Empirical risk minimization
Definition
Empirical Risk Minimization (ERM) is the standard objective function for training …
Embodied cognitive science
Definition
This field challenges traditional views that treat the mind as a computer processing …
Double Descent
Definition
Double descent challenges the traditional bias-variance tradeoff by showing that highly …
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 …
Bayesian interpretation of kernel regularization
Definition
This concept establishes that minimizing a regularized risk functional with a specific …
Attributional Calculus
Definition
Attributional calculus is a branch of modal logic focused on reasoning about epistemic …
Artificial general intelligence
Definition
Artificial General Intelligence (AGI) refers to a type of AI that can perform any …
Aporia
Definition
In philosophy and AI theory, aporia describes a paradoxical situation where two equally …
Algorithmic probability
Definition
Algorithmic probability, rooted in Kolmogorov complexity and Solomonoff induction, …
AIXI
Definition
AIXI is a theoretical framework proposed by Marcus Hutter that defines an idealized …
AI-complete
Definition
AI-complete problems are tasks that, if solved, would imply the existence of Artificial …
A Logical Calculus of the Ideas Immanent in Nervous Activity
Definition
This foundational paper proposed a mathematical model of neural networks, demonstrating …
Understanding
Definition
AI understanding goes beyond statistical correlation to interpret the underlying meaning …
Self
Definition
While current AI lacks consciousness, the term ‘self’ often describes …
Latent
Definition
In machine learning, latent variables are unobserved factors that influence observed …
Information
Definition
In the context of AI and computer science, information is distinct from raw data. It …
Group
Definition
In mathematics and theoretical computer science, a group is a set G together with a …
Global
Definition
The term ‘global’ in AI typically contrasts with ’local,’ …
Energy
Definition
Energy has two primary meanings in AI. First, it denotes the electrical power required to …