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Low-discrepancy sequence
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Related lectures (11)
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Stochastic Simulation: Uncertainty Quantification
Explores uncertainty quantification using Quasi Monte Carlo methods and discrepancy measures for integral approximation and volume estimation.
Discrepancy Function: Estimation and Applications
Explores estimating discrepancy functions and their practical applications in generating sets with low discrepancy.
Stochastic Simulation: Markov Chains and Monte Carlo
Covers Markov chains, Monte Carlo methods, low discrepancy sequences, and multidimensional integrals computation.
Random Number Generation: Deterministic Sequences in C++
Covers the implementation of deterministic random number generation in C++ simulations.
Randomness Extraction: Significance and Applications
Explores randomness extraction in cryptography, total variation distance, k-sources, and the Chernoff Bound theorem.
Applied Cryptography: Basics
Introduces applied cryptography basics, historical encryption methods, and the concept of perfect secrecy with the One Time Pad.
Number Sequences: Guessing, Fibonacci, Recurrence Relations
Covers the identification of number sequences and solving recurrence relations.
Number Sequences: Guessing, Modeling, and Solving Recurrence Relations
Covers the identification of number sequences, modeling population growth, and solving recurrence relations.
Python Programming: Sorting and Indexing
Covers Python programming concepts related to sorting and indexing.
Network Security: IP Security
Covers IP basics, vulnerabilities like IP spoofing, and the use of IPSec for Virtual Private Networks.
Random Number Generators: Modulo Generator
Explores random number generators on computers, focusing on the Modulo generator and the criteria for pseudo random numbers.
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