BeautifulAlgorithms.jl
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Concise algorithms written in Julia and formatted with Carbon.
Algorithms for machine learning, optimization, reinforcement learning, online planning, decision making under uncertainty, and sorting. All implementations are working and self-contained; refer to the test cases.
Note, these are primarily for academic purposes and are not designed for real-world usage. There are many other Julia packages that implement more sound versions of these algorithms.
] add http://github.com/mossr/BeautifulAlgorithms.jlNote: Algorithms are modified from their original sources.
Gradient descent
Percy Liang and Dorsa Sadigh, Artificial Intelligence: Principles and Techniques, Stanford University, 2019.
Stochastic gradient descent
Percy Liang and Dorsa Sadigh, Artificial Intelligence: Principles and Techniques, Stanford University, 2019.
K-means clustering
Percy Liang and Dorsa Sadigh, Artificial Intelligence: Principles and Techniques, Stanford University, 2019.
The EM algorithm
Andrew Ng, Mixtures of Gaussians and the EM algorithm, Stanford University, 2020.1
Linear regression
Mykel J. Kochenderfer and Tim A. Wheeler, Algorithms for Optimization, MIT Press, 2019. (Credit @HenriDeh for use of ones)
Linear regression (one-liner)
Basis regression
Mykel J. Kochenderfer and Tim A. Wheeler, Algorithms for Optimization, MIT Press, 2019.
Radial basis regression
Mykel J. Kochenderfer and Tim A. Wheeler, Algorithms for Optimization, MIT Press, 2019.
Cross-entropy method
Mykel J. Kochenderfer and Tim A. Wheeler, Algorithms for Optimization, MIT Press, 2019.
Finite difference methods
Mykel J. Kochenderfer and Tim A. Wheeler, Algorithms for Optimization, MIT Press, 2019.
Simulated annealing
Mykel J. Kochenderfer and Tim A. Wheeler, Algorithms for Optimization, MIT Press, 2019.
Gaussian process
Mykel J. Kochenderfer and Tim A. Wheeler, Algorithms for Optimization, MIT Press, 2019.
Thompson sampling
Daniel J. Russo, Benjamin Van Roy, Abbas Kazerouni, Ian Osband, and Zheng Wen, A Tutorial on Thompson Sampling, arXiv:1707.02038, 2020.
Particle filter
Mykel J. Kochenderfer, Tim A. Wheeler, and Kyle H. Wray, Algorithms for Decision Making, Preprint.
Value iteration
Mykel J. Kochenderfer, Tim A. Wheeler, and Kyle H. Wray, Algorithms for Decision Making, Preprint.
Branch and bound
Mykel J. Kochenderfer, Tim A. Wheeler, and Kyle H. Wray, Algorithms for Decision Making, Preprint.
Monte Carlo tree search
Mykel J. Kochenderfer, Tim A. Wheeler, and Kyle H. Wray, Algorithms for Decision Making, Preprint.
Huffman coding
David A. Huffman, A Method for the Construction of Minimum-Redundancy Codes, IEEE, 1952.
