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Computing using random bit streams
bits. Complex computations can then be computed by simple bit-wise operations on the streams. Stochastic computing is distinct from the study of randomized
Stochastic_computing
Computing by new or unusual methods
Unconventional computing (also known as alternative computing or nonstandard computation) is computing by any of a wide range of new or unusual methods
Unconventional_computing
Concept in network science
The stochastic block model is a generative model for random graphs. This model tends to produce graphs containing communities, subsets of nodes characterized
Stochastic_block_model
American computer scientist
Alaghi, A.; Hayes, J. P. (2013). "Survey of Stochastic Computing". ACM Transactions on Embedded Computing Systems. 12 (2s): 1. doi:10.1145/2465787.2465794
John_P._Hayes
Term used in machine learning
In machine learning, the term stochastic parrot is a metaphor that frames large language models as systems that statistically mimic text without real understanding
Stochastic_parrot
Device that selects between several analog or digital input signals
Architecture with Sequential Logic-Based Stochastic Computing". ACM Journal on Emerging Technologies in Computing Systems. 13 (4): 57:1–57:28. doi:10.1145/3060537
Multiplexer
Collection of random variables
In probability theory and related fields a stochastic (/stəˈkæstɪk/) or random process is a mathematical object usually defined as a family of random variables
Stochastic_process
Optimization algorithm
better than "true" stochastic gradient descent described, because the code can make use of vectorization libraries rather than computing each step separately
Stochastic_gradient_descent
Optimization method
Stochastic optimization (SO) are optimization methods that generate and use random variables. For stochastic optimization problems, the objective functions
Stochastic_optimization
Computer hardware technology that uses quantum mechanics
information in quantum computing, the qubit (quantum bit), serves a similar function as the bit in ordinary or "classical" computing. Unlike a classical
Quantum_computing
Unconventional logic circuit
any synchronicity among them. This is useful in stochastic computing, also known as Random Pulse Computing (RPC)[1], where many information-processing circuits
Random_flip-flop
Topics referred to by the same term
Convolution kernel Stochastic kernel, the transition function of a stochastic process Transition kernel, a generalization of a stochastic kernel Pricing kernel
Kernel
Computer simulation with random inputs
A stochastic simulation is a simulation of a system that has variables that can change stochastically (randomly) with individual probabilities. Realizations
Stochastic_simulation
Family of iterative methods
values of functions which cannot be computed directly, but only estimated via noisy observations. In a nutshell, stochastic approximation algorithms deal with
Stochastic_approximation
Series of activities
population Diffusion process, a solution to a stochastic differential equation Empirical process, a stochastic process that describes the proportion of objects
Process
1957 technique for modelling problems of decision making under uncertainty
Originally introduced by Richard E. Bellman in (Bellman 1957), stochastic dynamic programming (SDP) is a technique for modelling and solving problems of
Stochastic dynamic programming
Stochastic_dynamic_programming
Matrix used to describe the transitions of a Markov chain
In mathematics, a stochastic matrix is a square matrix used to describe the transitions of a Markov chain. Each of its entries is a nonnegative real number
Stochastic_matrix
Family of optimization algorithms
(Stochastic) variance reduction is an algorithmic approach to minimizing functions that can be decomposed into finite sums. By exploiting the finite sum
Stochastic_variance_reduction
Calculus of stochastic differential equations
calculus to stochastic processes such as Brownian motion (see Wiener process). It has important applications in mathematical finance, in stochastic differential
Itô_calculus
Study of random spatial patterns
In mathematics, stochastic geometry is the study of random spatial patterns. At the heart of the subject lies the study of random point patterns. This
Stochastic_geometry
Computer providing a central resource or service
large computing clusters may also be composed of many relatively simple, replaceable server components. The use of the word server in computing comes
Server_(computing)
resulting from the stochastic nature of modern computers. Unlike traditional computer forensics, which relies on digital artifacts, stochastic forensics does
Stochastic_forensics
Refinement of ray tracing that allows for the rendering of "soft" phenomena
technique, or the term parallel ray tracing in reference to parallel computing. Global illumination Monte Carlo method Ray tracing Stochastic rasterization
Distributed_ray_tracing
Random process independent of past history
probability theory and statistics, a Markov chain or Markov process is a stochastic process describing a sequence of possible events in which the probability
Markov_chain
Probability modelling tool
stochastic modelling as applied to the insurance industry. For other stochastic modelling applications, please see Monte Carlo method and Stochastic asset
Stochastic modelling (insurance)
Stochastic_modelling_(insurance)
When variance is a random variable
In statistics, stochastic volatility models are those in which the variance of a stochastic process is itself randomly distributed. They are used in the
Stochastic_volatility
Computational model used in machine learning
images. Unsupervised pre-training and increased computing power from GPUs and distributed computing allowed the use of larger networks, particularly
Neural network (machine learning)
Neural_network_(machine_learning)
Real-Number Complexity Special Functions and Orthogonal Polynomials Stochastic Computing Symbolic Analysis The Society for the Foundations of Computational
Foundations of Computational Mathematics
Foundations_of_Computational_Mathematics
Probability and Statistics Combinatorics, Probability and Computing Communications on Stochastic Analysis Electronic Communications in Probability Electronic
List_of_probability_journals
Concept in software engineering and computer science
Ubiquitous computing (or "ubicomp") is a concept in software engineering, hardware engineering and computer science where computing is made to appear seamlessly
Ubiquitous_computing
Field of statistical mechanics
Stochastic thermodynamics is an emergent field of research in statistical mechanics that uses stochastic variables to better understand the non-equilibrium
Stochastic_thermodynamics
Economic model of personal preferences
In economics, a random utility model (RUM), also called stochastic utility model, is a mathematical description of the preferences of a person, whose choices
Random_utility_model
ligand-protein binding) is computed efficiently and accurately with stochastic roadmap simulation. PFold values are computed using the first step analysis
Stochastic_roadmap_simulation
Neumann (1903–1957), Hungary – Von Neumann computer architecture, Stochastic computing, Merge sort algorithm Isaac Newton (1642–1727), UK – reflecting telescope
List_of_inventors
Mathematical techniques used in probability theory and related fields
mathematical finance to compute the sensitivities of financial derivatives. The calculus has applications in, for example, stochastic filtering. Malliavin
Malliavin_calculus
Replacing a number with a simpler value
, to a multiple of 0.01) entails computing 2.1784 / 0.01 = 217.84, then rounding that to 218, and finally computing 218 × 0.01 = 2.18. When rounding to
Rounding
advancements aimed to make DNA computing devices accessible through a compiler bridging high-level programming languages with DNA computing code. Shapiro and Ran
Doctor_in_a_cell
Problems involving random attributes
Stochastic scheduling concerns scheduling problems involving random attributes, such as random processing times, random due dates, random weights, and
Stochastic_scheduling
Iranian electrical engineer and computer scientist
electrical engineer and computer scientist who studies networked information, stochastic control, machine learning, hypothesis testing, network optimization, and
Tara_Javidi
Stochastic multicriteria acceptability analysis (SMAA) is a multiple-criteria decision analysis method for problems with missing or incomplete information
Stochastic multicriteria acceptability analysis
Stochastic_multicriteria_acceptability_analysis
Technique for dimensionality reduction
t-distributed stochastic neighbor embedding (t-SNE) is a statistical method for visualizing high-dimensional data by giving each datapoint a location in
T-distributed stochastic neighbor embedding
T-distributed_stochastic_neighbor_embedding
British scientist and engineer
systems theory. Gaines is one of the pioneers in what is known as stochastic computing, a term he used first to characterise the highly attractive field
Brian_R._Gaines
British statistician (1960–2019)
paper “Bayesian inference for a stochastic kinetic model” was featured in the scientific journal Statistics in Computing in 2008. The paper outlined how
Richard_James_Boys
Taylor series expansion in probability theory
a real stochastic process, one can compute its central-moment functions from experimental data on the process, from which one can then compute its Kramers–Moyal
Kramers–Moyal_expansion
Interpretation of quantum mechanics
Stochastic quantum mechanics is a framework for describing the dynamics of particles that are subjected to intrinsic random processes as well as various
Stochastic_quantum_mechanics
Method by which work is assigned
In computing, scheduling is the action of assigning resources to perform tasks. The resources may be processors, network links or expansion cards. The
Scheduling_(computing)
Optimization algorithm for artificial neural networks
network in computing parameter updates. It is an efficient application of the chain rule to neural networks. Backpropagation efficiently computes the gradient
Backpropagation
Topics referred to by the same term
transition system in computing, which may refer more specifically to a Turing machine, finite-state machine, or cellular automaton a stochastic kernel In statistics
Transition_function
Global computing organization
1 Computers and Work WG 9.2 Social Accountability and Computing SIG 9.2.2 Ethics and Computing WG 9.3 Home-Oriented Informatics and Telematics - HOIT
International Federation for Information Processing
International_Federation_for_Information_Processing
When the occurrence of one event does not affect the likelihood of another
statistics and the theory of stochastic processes. Two events are independent, statistically independent, or stochastically independent if, informally speaking
Independence (probability theory)
Independence_(probability_theory)
Branch of mathematics
not close the problem since the theorem does not provide any way for computing the solutions. Linear algebra starts with the study of systems of linear
Algebra
Class of stochastic process
strict/strictly stationary process or strong/strongly stationary process) is a stochastic process whose statistical properties, such as mean and variance, do not
Stationary_process
Framework for modeling optimization problems that involve uncertainty
mathematical optimization, stochastic programming is a framework for modeling optimization problems that involve uncertainty. A stochastic program is an optimization
Stochastic_programming
Concept in financial economics
price of an asset being computable by "discounting" the future cash flow x ~ i {\displaystyle {\tilde {x}}_{i}} by the stochastic factor m ~ {\displaystyle
Stochastic_discount_factor
Mathematical topics based on the works of George Boole
Boolean values or operators Boolean model (probability theory), a model in stochastic geometry Boolean network, a certain network consisting of a set of Boolean
Boolean
Class of financial models with stochastic volatility and jumps
Stochastic Volatility Jump Models (SVJ models) are a class of mathematical models in quantitative finance that combine stochastic volatility dynamics
Stochastic volatility jump models
Stochastic_volatility_jump_models
Decentralized machine learning
nodes for each iteration diminishes computing cost and may prevent overfitting, in the same way that stochastic gradient descent can reduce overfitting
Federated_learning
Deep backward stochastic differential equation method is a numerical method that combines deep learning with Backward stochastic differential equation
Deep backward stochastic differential equation method
Deep_backward_stochastic_differential_equation_method
Network that allows computers to share resources and communicate with each other
tunnel between the SSL server and the SSL client. Cloud computing Cyberspace Distributed computing History of the Internet Information Age ISO/IEC 11801 –
Computer_network
Chinese mathematician
mathematical and computational results in stochastic differential equations; design of efficient algorithms to compute multiscale and multiphysics problems
Weinan_E
Computational problem of graph theory
Proceedings of the 57th Annual ACM Symposium on Theory of Computing (STOC). Association for Computing Machinery. pp. 36–44. doi:10.1145/3717823.3718179.
Shortest_path_problem
Stochastic method of global optimization
In numerical analysis, stochastic tunneling (STUN) is an approach to global optimization based on the Monte Carlo method-sampling of the function to be
Stochastic_tunneling
Trial and error problem solvers with a metaheuristic or stochastic optimization character
Evolutionary computing as a field began in earnest in the 1950s and 1960s. There were several independent attempts to use the process of evolution in computing at
Evolutionary_computation
Statistical model
In probability theory and statistics, a Gaussian process is a stochastic process (a collection of random variables indexed by time or space), such that
Gaussian_process
networks. Proc ACM Symposium on Applied Computing (Madrid). 574–577. Jones, D. (2002). Constrained Stochastic Diffusion Search. SCARP 2002, University
Stochastic_diffusion_search
Computer system simulating intelligence
soft computing techniques, which are used in artificial intelligence on the one hand and computational intelligence on the other. In hard computing (HC)
Computational_intelligence
Type of simulation
random variables that need to be characterized to model this system stochastically are the interarrival-time for recurrent customer-arrival events and
Discrete-event_simulation
Study of mathematical algorithms for optimization problems
by systematically choosing input values from within an allowed set and computing the value of the function. The generalization of optimization theory and
Mathematical_optimization
Probabilistic problem-solving algorithm
Scientific Computing. Fortran Numerical Recipes. Vol. 1 (2nd ed.). Cambridge University Press. ISBN 978-0-521-43064-7. Ripley, B. D. (1987). Stochastic Simulation
Monte_Carlo_method
Topics referred to by the same term
long-running transactions (on distributed computing) Simple API for Grid Applications (SAGA), a standard for distributed computing from the Open Grid Forum Sexuality
Saga_(disambiguation)
In probability theory, Lévy's stochastic area is a stochastic process that describes the enclosed area of a trajectory of a two-dimensional Brownian motion
Lévy's_stochastic_area
Mathematical model for sequential decision making under uncertainty
outcomes are uncertain. It is a type of stochastic decision process, and is often solved using the methods of stochastic dynamic programming. Originating from
Markov_decision_process
Tree data structure that partitions a 2D area
with random insertion have been studied under the name weighted planar stochastic lattices. Point quadtrees are constructed as follows. Given the next point
Quadtree
Mathematical model
theory of probability, a fluid queue (fluid model, fluid flow model or stochastic fluid model) is a mathematical model used to describe the fluid level
Fluid_queue
Construction for generating graphs for modeling systems
benchmark for supercomputers is based on the use of a stochastic version of Kronecker graphs. Stochastic kronecker graph is a kronecker graph with each component
Kronecker_graph
American mathematician
Association for Computing Machinery (ACM), for his contributions in numerical linear algebra, computational science, parallel computing, and random matrix
Alan_Edelman
Norwegian research foundation
July 2013 BigInsight Norsk Regnesentral / Norwegian Computing Center (homepage) Norwegian Computing Center's annual public reports Tribute to Kristen Nygaard
Norwegian_Computing_Center
Combined real-and-virtual environment
glasses Spatial computing – Computing paradigm emphasizing 3D spatial interaction with technology Wearable computer – Small computing device worn on the
Extended_reality
Base of natural logarithms
methods for computing the exponential function, it is impractical because of high overhead cost. Tools such as y-cruncher are optimized for computing many digits
E_(mathematical_constant)
Approximate nearest neighbor search algorithm
Exponential random (ERGM) Random geometric (RGG) Hyperbolic (HGN) Hierarchical Stochastic block Blockmodeling Maximum entropy Soft configuration LFR Benchmark Dynamics
Hierarchical navigable small world
Hierarchical_navigable_small_world
Type of physical or mathematical property
equations are invariant or symmetrical under a change in the sign of time. A stochastic process is reversible if the statistical properties of the process are
Time_reversibility
Method of machine learning
maximize ad revenue, portfolio optimization, shortest path prediction (with stochastic weights, e.g. traffic on roads for a maps application), spam filtering
Online_machine_learning
2598–2605. Chen, Chun-Hung; Lee, Loo H. (2011). Stochastic Simulation Optimization: An Optimal Computing Budget Allocation. World Scientific Series on Nonlinear
Optimal computing budget allocation
Optimal_computing_budget_allocation
Mechanical engineer
Discrete Structures: Purposeful Design of Grammatical Structures by Directed Stochastic Search, was supervised by Jonathan Cagan. Shea came to Switzerland as
Kristina_Shea
Randomized transitivity in paired comparisons
Stochastic transitivity models are stochastic versions of the transitivity property of binary relations studied in mathematics. Several models of stochastic
Stochastic_transitivity
Statistical tool to model changing systems
In probability theory, a Markov model is a stochastic model used to model pseudo-randomly changing systems. It is assumed that future states depend only
Markov_model
Method for problem solving in optimization
search, on memory, like reactive search optimization, on memory-less stochastic modifications, like simulated annealing. Local search does not provide
Local_search_(optimization)
Press. ASIN B004JN0UIQ Antoine Petrus Cornelius van der Ploeg (2006).Stochastic volatility and the pricing of financial derivatives. University of Amsterdam
Volatility_risk_premium
Standard hostname for a networked device's loopback interface
controller (NIC) or hardware device driver and must not appear outside of a computing system, or be routed by any router. This permits software testing and
Localhost
Branch of mathematics
identify the best path to follow taking that uncertainty into account. Stochastic tunneling (STUN) is an approach to global optimization based on the Monte
Global_optimization
Formula relating stochastic processes to partial differential equations
differential equations by simulating random paths of a stochastic process. Conversely, it can be used to compute an important class of expectations of random processes
Feynman–Kac_formula
American industrial engineer
Research and Management Sciences (INFORMS) Computing Society Prize for Pyomo, and the 2021 INFORMS Computing Society Distinguished Service Award. Among
David_L._Woodruff
Form of cloud computing
Mobile Cloud Computing (MCC) is the combination of cloud computing and mobile computing to bring rich computational resources to mobile users, network
Mobile_cloud_computing
(MLMC) methods in numerical analysis are algorithms for computing expectations that arise in stochastic simulations. Just as Monte Carlo methods, they rely
Multilevel_Monte_Carlo_method
Mathematical study of waiting lines, or queues
have since seen applications in telecommunications, traffic engineering, computing, project management, and particularly industrial engineering, where they
Queueing_theory
Medical imaging procedure
large part to the killing/malfunction of cells following high doses; stochastic effects, i.e., cancer and heritable effects involving either cancer development
CT_scan
Professor of Computing Science at Imperial College London known for the reversed compound agent theorem, which gives conditions for a stochastic network to
Peter_G._Harrison
Process of arranging, controlling and optimizing work and workloads
Single-machine scheduling Schedule (project management) Scheduling (computing) Stochastic scheduling Marcus V. Magalhaes and Nilay Shah, “Crude Oil Scheduling
Scheduling (production processes)
Scheduling_(production_processes)
Variable representing a random phenomenon
A random variable (also called random quantity, aleatory variable, or stochastic variable) is a mathematical formalization of a quantity or object which
Random_variable
Exponential representation for differential equations
Pascucci, A. (2021). "On the Stochastic Magnus Expansion and Its Application to SPDEs". Journal of Scientific Computing. 89 (3): 56. arXiv:2001.01098
Magnus_expansion
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STOCHASTIC COMPUTING
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