User:Waterbug89/Books/Stochastic applications, methods, algorithms
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Stochastic applications, methods, algorithms
stochastic analysis
- Algorithmic information theory
- Antithetic variates
- Approximate counting algorithm
- Arthur–Merlin protocol
- Atlantic City algorithm
- Automatic basis function construction
- Auxiliary field Monte Carlo
- Auxiliary particle filter
- Average-case complexity
- Biology Monte Carlo method
- Bloom filter
- BRST algorithm
- CASINO
- CMA-ES
- Construction of an irreducible Markov chain in the Ising model
- Count–min sketch
- Coupling from the past
- Cross-entropy method
- Datar–Mathews method for real option valuation
- Demon algorithm
- Derandomization
- Diffusion Monte Carlo
- Direct simulation Monte Carlo
- Dynamic Monte Carlo method
- Ensemble forecasting
- Ensemble Kalman filter
- Equation of State Calculations by Fast Computing Machines
- Estimation of distribution algorithm
- Expected linear time MST algorithm
- Fisher–Yates shuffle
- Freivalds' algorithm
- Gaussian quantum Monte Carlo
- Gibbs sampling
- Gillespie algorithm
- Hybrid Monte Carlo
- HyperLogLog
- Inverse transform sampling
- Iterated filtering
- Karloff–Zwick algorithm
- Kinetic Monte Carlo
- Least mean squares filter
- Linear partial information
- Linear–quadratic–Gaussian control
- List update problem
- Locality-sensitive hashing
- Low-energy adaptive clustering hierarchy
- Mabinogion sheep problem
- Markov chain Monte Carlo
- Markov decision process
- Marsaglia polar method
- Mean field particle methods
- Merton's portfolio problem
- Metropolis light transport
- Metropolis-adjusted Langevin algorithm
- Metropolis–Hastings algorithm
- Monte Carlo algorithm
- Monte Carlo integration
- Monte Carlo localization
- Monte Carlo method
- Monte Carlo method for photon transport
- Monte Carlo methods for electron transport
- Monte Carlo methods for option pricing
- Monte Carlo methods in finance
- Monte Carlo molecular modeling
- Monte Carlo tree search
- Morris method
- MPMC
- Multi-armed bandit
- Multiplier uncertainty
- Natural evolution strategy
- Neyer d-optimal test
- Partially observable Markov decision process
- Path integral Monte Carlo
- PCP theorem
- Pocock boundary
- Principle of deferred decision
- Quantum Monte Carlo
- Quasi-Monte Carlo method
- Quasi-Monte Carlo methods in finance
- Quotient filter
- Random binary tree
- Random permutation
- Random search
- Random self-reducibility
- Random tree
- Randomized algorithm
- Randomized algorithms as zero-sum games
- Rapidly-exploring random tree
- Rejection sampling
- Reptation Monte Carlo
- Resampling (statistics)
- Reservoir sampling
- Response surface methodology
- Reverse Monte Carlo
- Reversible-jump Markov chain Monte Carlo
- Scenario optimization
- Separation principle
- Set balancing
- Simulated annealing
- Simulation Optimization Library: Throughput Maximization
- Simultaneous perturbation stochastic approximation
- Sipser–Lautemann theorem
- Slice sampling
- Solovay–Strassen primality test
- Stochastic approximation
- Stochastic computing
- Stochastic gradient descent
- Stochastic neural network
- Stochastic optimization
- Stochastic tunneling
- Stochastic universal sampling
- Swendsen–Wang algorithm
- Tau-leaping
- Thompson sampling
- Time-dependent variational Monte Carlo
- Transition path sampling
- TraPPE force field
- Treap
- Umbrella sampling
- Variance reduction
- Variational Monte Carlo
- Volumetric path tracing
- Wang and Landau algorithm
- With high probability
- Witsenhausen's counterexample
- Wolff algorithm
- Yao's principle
- Ziff–Gulari–Barshad model