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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
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
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
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
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
1957 technique for modelling problems of decision making under uncertainty
programming, stochastic dynamic programming represents the problem under scrutiny in the form of a Bellman equation. The aim is to compute a policy prescribing
Stochastic dynamic programming
Stochastic_dynamic_programming
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
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
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
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
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
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
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
Rewriting system and type of formal grammar
context-sensitive stochastic L-systems is possible if inferring context-free L-system is possible. Stochastic L-Systems (S0L): For stochastic L-systems, PMIT-S0L
L-system
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
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
Hungarian and American mathematician and physicist (1903–1957)
subtly incorrect. Stochastic computing was introduced by von Neumann in 1953 and could not be implemented until advances in computing of the 1960s. Around
John_von_Neumann
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)
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
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
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
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
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
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)
Neumann (1903–1957), Hungary – Von Neumann computer architecture, Stochastic computing, Merge sort algorithm Isaac Newton (1642–1727), UK – reflecting telescope
List_of_inventors
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)
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
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
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
Probability and Statistics Combinatorics, Probability and Computing Communications on Stochastic Analysis Electronic Communications in Probability Electronic
List_of_probability_journals
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
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
resulting from the stochastic nature of modern computers. Unlike traditional computer forensics, which relies on digital artifacts, stochastic forensics does
Stochastic_forensics
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
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
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
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
Trial and error problem solvers with a metaheuristic or stochastic optimization character
population-based trial and error problem solvers with a metaheuristic or stochastic optimization character. In evolutionary computation, an initial set of
Evolutionary_computation
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
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
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
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
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
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
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
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
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
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)
Israeli mathematician and management scientist (born 1971)
and David Shmoys. His dissertation was entitled "Computing Provably Near-Optimal Policies for Stochastic Inventory Control Models". Professors James Renegar
Retsef_Levi
Statistical tool to model changing systems
through Hierarchical Stochastic Learning". PERCOM '03 Proceedings of the First IEEE International Conference on Pervasive Computing and Communications.
Markov_model
Private deep learning via gradient clipping
Differentially private stochastic gradient descent (DP-SGD) is an algorithmic technique for learning and a refined analysis of privacy costs within the
Differentially private stochastic gradient descent
Differentially_private_stochastic_gradient_descent
ligand-protein binding) is computed efficiently and accurately with stochastic roadmap simulation. PFold values are computed using the first step analysis
Stochastic_roadmap_simulation
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
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
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
Type 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
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
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
networks. Proc ACM Symposium on Applied Computing (Madrid). 574–577. Jones, D. (2002). Constrained Stochastic Diffusion Search. SCARP 2002, University
Stochastic_diffusion_search
American mathematician
Association for Computing Machinery (ACM), for his contributions in numerical linear algebra, computational science, parallel computing, and random matrix
Alan_Edelman
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)
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
2.71828...; 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)
Variation of classical electrodynamics
Stochastic electrodynamics (SED) extends classical electrodynamics (CED) of theoretical physics by adding the hypothesis of a classical Lorentz invariant
Stochastic_electrodynamics
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
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
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
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
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
Ability of a computing system to simulate Turing machines
information theory Chomsky hierarchy Church–Turing thesis Computability theory Inner loop Loop (computing) Machine that always halts Rice's theorem S m n theorem
Turing_completeness
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
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)
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
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
Chinese mathematician
mathematical and computational results in stochastic differential equations; design of efficient algorithms to compute multiscale and multiphysics problems
Weinan_E
German-Canadian computer scientist (born 1969)
(EurAI) as well as a Fellow of the Association for Computing Machinery (ACM). He wrote the book Stochastic Local Search: Foundations and Applications (with
Holger_H._Hoos
(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
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
Form of calculus
Quantum stochastic calculus is a generalization of stochastic calculus to noncommuting variables. The tools provided by quantum stochastic calculus are
Quantum_stochastic_calculus
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
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
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
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)
Theorem on changes in stochastic processes
Girsanov's theorem or the Cameron-Martin-Girsanov theorem explains how stochastic processes change under changes in measure. The theorem is especially important
Girsanov_theorem
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
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
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
American computer scientist (born 2000)
for other problems, such as principal component analysis and low-rank stochastic regression. Before Tang's undergraduate thesis, the best known classical
Ewin_Tang
Resource problem in machine learning
The multi-armed bandit problem also falls into the broad category of stochastic scheduling. In the problem, each machine provides a random reward from
Multi-armed_bandit
Type of feedforward neural network
2013 a technique called stochastic pooling, the conventional deterministic pooling operations were replaced with a stochastic procedure, where the activation
Convolutional_neural_network
Correlation of a signal with a time-shifted copy of itself, as a function of shift
algorithms exist which can compute the autocorrelation in order n log(n). For example, the Wiener–Khinchin theorem allows computing the autocorrelation from
Autocorrelation
Macroeconomic method
Dynamic stochastic general equilibrium modeling (abbreviated as DSGE, or DGE, or sometimes SDGE) is a macroeconomic method which is often employed by monetary
Dynamic stochastic general equilibrium
Dynamic_stochastic_general_equilibrium
Stochastic volatility model used in derivatives markets
model is a stochastic volatility model, which attempts to capture the volatility smile in derivatives markets. The name stands for "stochastic alpha, beta
SABR_volatility_model
Statistical Markov model
{\displaystyle X_{n}} and Y n {\displaystyle Y_{n}} be discrete-time stochastic processes and n ≥ 1 {\displaystyle n\geq 1} . The pair ( X n , Y n ) {\displaystyle
Hidden_Markov_model
Model in finance
describes the evolution of the volatility of an underlying asset. It is a stochastic volatility model: such a model assumes that the volatility of the asset
Heston_model
Overview of and topical guide to machine learning
Stephen Wolfram Stochastic block model Stochastic cellular automaton Stochastic diffusion search Stochastic grammar Stochastic matrix Stochastic universal sampling
Outline_of_machine_learning
STOCHASTIC COMPUTING
STOCHASTIC COMPUTING
STOCHASTIC COMPUTING
STOCHASTIC COMPUTING
Boy/Male
Muslim/Islamic
Slave of the Acceptor of repentance the relenting
Boy/Male
Hindu, Indian, Malayalam, Marathi, Sindhi
Mountain of Gold
Girl/Female
Hindu
River bank
Boy/Male
Hindu
The Moon
Female
English
English name derived from the title, itself from Old French princesse, a feminine form of Prince, PRINCESS means "chief, first."
Boy/Male
Bengali, Gujarati, Hindu, Indian, Kannada, Malayalam, Marathi, Telugu
Light of the World
Girl/Female
Arabic, Muslim
Mermaid; Beautiful
Surname or Lastname
English
English : variant of Chandley.
Boy/Male
Tamil
Rich Man
Girl/Female
Hindu
Lord Shiva
STOCHASTIC COMPUTING
STOCHASTIC COMPUTING
STOCHASTIC COMPUTING
STOCHASTIC COMPUTING
STOCHASTIC COMPUTING
v. i.
To make an enumeration or computation; to engage in numbering or computing.
n.
One of the ten figures or symbols, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, by which all numbers are expressed; -- so called because of the use of the fingers in counting and computing.
p. p. & a.
Worked out by calculation; as calculated tables for computing interest; ascertained or conjectured as a result of calculation; as, the calculated place of a planet; the calculated velocity of a cannon ball.
n.
The act or process of computing; calculation; reckoning.
n.
A system of numbers, whose denominations rise in a scale of twelves, as of feet and inches. The system is used chiefly by artificers in computing the superficial and solid contents of their work.
n.
An instrument for measuring the intensity of the photogenic (light-producing) rays, and computing the power of object glasses.
p. pr. & vb. n.
of Compute
n.
A contrivance for computing the revolutions of a wheel; an odometer.
n.
The computing official of an insurance company; one whose profession it is to calculate for insurance companies the risks and premiums for life, fire, and other insurances.
a.
Conjectural; able to conjecture.
n.
The art of measuring and computing the cubical contents of bodies and figures; -- distinguished from planimetry.
n.
An arbitrary fixed date, for which the elements used in computing the place of a planet, or other heavenly body, at any other date, are given; as, the epoch of Mars; lunar elements for the epoch March 1st, 1860.
n.
A quantity to be applied in computing the mean place or other element of a celestial body; that is, any one of the several quantities to be added to, or taken from, its position as calculated on the hypothesis of a mean uniform motion, in order to find its true position as resulting from its actual and unequal motion.