Resource constraint - A resource constraint is a restriction imposed by the limited availability of something required to perform an activity.
Respondent error - Respondent error is a component of survey measurement error arising when a respondent gives an incorrect answer, deliberately or inadvertently.
Response - A response is the output a generative AI model or application returns in reaction to its input.
Response Bias - Response bias is a systematic distortion in the answers people provide, causing recorded responses to differ from what the study intends to measure.
Response modeling methodology - Response modeling methodology, abbreviated RMM, is a named empirical modeling framework developed by Haim Shore for representing systematic response...
Response set - A response set is the collection of outputs produced by a language model for a corresponding collection of prompts.
Response surface model - A response surface model is a mathematical approximation describing how a response changes with two or more input factors over a specified region.
Responsible AI - Responsible AI is the practice of developing, deploying, using, and governing AI with attention to its effects on people, society, and the environment.
Restricted Boltzmann Machine - A restricted Boltzmann machine, or RBM, is an energy-based probabilistic model with visible units representing observed data and hidden units representing...
Restricted mean survival time - Restricted mean survival time, or RMST, is the expected time spent event-free up to a specified time horizon tau.
Restricted randomization - Restricted randomization is random assignment carried out within predefined constraints rather than over every otherwise possible allocation.
Rete - Rete is an algorithm for efficiently matching many rule conditions against a changing collection of facts.
Retention limit - A retention limit is a defined boundary on how long data or records are kept for a particular purpose.
Retention period - A retention period is the length of time information or records must or should be kept under an applicable retention rule.
Retrace(lambda) - Retrace(lambda) is a multi-step off-policy reinforcement-learning method that combines target-policy temporal-difference errors using truncated...
Retraining - Retraining updates a previously trained machine-learning model through another training process using different training data.
Retrievability - Retrievability describes how readily a particular document can appear in the results produced by an information retrieval system.
Retrieval-augmented generation - Retrieval-augmented generation, usually shortened to RAG, is a way of giving an AI model relevant information before it generates an answer.
Retrospective study - A retrospective study investigates events or information that already existed when the study was designed or initiated.
Return - In reinforcement learning, the return is the total reward an agent collects from a point onward, usually with future rewards discounted, and it is the...
Revelation principle - The revelation principle is a mechanism-design result showing that an outcome achievable through an appropriate equilibrium of a mechanism can also be...
Revenue equivalence theorem - The revenue equivalence theorem states that, under specified auction-model assumptions, mechanisms with the same allocation probabilities and the same...
Reverse data management - Reverse data management starts with a desired result or condition and asks what changes to underlying data would produce it.
Reverse-search algorithm - A reverse-search algorithm is an enumeration method that generates objects by traversing an implicitly defined tree.
Reverse star schema - A reverse star schema is a subject-centered database organization in which a focal entity, such as a customer, connects to multiple kinds of activity or...
Reward - A reward is the numerical feedback signal that defines what a reinforcement learning agent is encouraged to achieve.
Reward hypothesis - The reward hypothesis is the proposal that goals and purposes can be represented through maximizing the expected cumulative value of a scalar reward signal.
Reward shaping - Reward shaping adds supplementary reward information to a reinforcement learning task to guide learning.
Reward-to-go - Reward-to-go is the cumulative reward remaining from a particular decision onward in a trajectory.
Rhetorical structure theory - Rhetorical structure theory, or RST, is a framework for describing how parts of a text contribute to its overall organization and coherence.
Rich Club - A rich club in a network is a set of highly connected nodes that also connect densely to one another.
Ridge detection - Ridge detection identifies elongated structures that are locally high or low relative to neighboring values across their width.
Ridge regression - Ridge regression is linear regression fitted with a penalty on the sum of squared coefficient values.
Riemann manifold Hamiltonian Monte Carlo - Riemann manifold Hamiltonian Monte Carlo is an MCMC method that uses a position-dependent metric to adapt Hamiltonian sampling dynamics to local features of...
Risk-averse - Risk-averse describes a decision maker who prefers a certain outcome to an uncertain prospect with the same expected outcome value.
Risk control - A risk control is a measure intended to modify a risk, such as reducing the likelihood of an unwanted event, limiting its consequences, or improving...
Risk-neutral - Risk-neutral describes a decision maker who compares uncertain prospects by their expected value in a specified outcome measure, without an additional...
Risk-seeking - Risk-seeking describes a decision maker who prefers an uncertain prospect to a certain outcome with the same expected value.
Risk set - A risk set is the collection of study subjects or units that are being observed and are eligible to experience a specified event at a particular time.
Risk stratification - Risk stratification is the process of assigning cases to groups based on estimated risk of a specified outcome.
Risk tolerance - Risk tolerance is the amount and type of uncertainty or potential harm that an organization or person is prepared to accept while pursuing an objective.
RMSNorm - RMSNorm, short for root mean square normalization, is a neural-network normalization operation that rescales a vector using the square root of its mean...
RNN-T - RNN-T stands for recurrent neural network transducer.
Roberts cross gradient operator - The Roberts cross gradient operator estimates local image-intensity change using two diagonal differences across a 2×2 neighborhood.
Robot as a service - Robot as a service, often abbreviated RaaS and also called robots or robotics as a service, commonly describes obtaining robotic capability through a...
Robot ethics - Robot ethics examines the moral questions raised by designing, building, deploying, and interacting with robots.
Robot learning - Robot learning is the use of data and experience to help a robot acquire or improve capabilities.