Reservoir sampling - Wikipedia
Reservoir sampling is a family of randomized algorithms for choosing a simple random sample, without replacement, of k items from a population of unknown size n in a single pass over the items. The size of the population n is not known to the algorithm and is typically too large for all n items to fit into main memory. The population is revealed to the algorithm over time, and the algorithm cannot
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Rabin-Karp string search algorithm - Wikipedia, the free encyclopedia
In computer science, the Rabin–Karp algorithm or Karp–Rabin algorithm is a string-searching algorithm created by Richard M. Karp and Michael O. Rabin (1987) that uses hashing to find an exact match of a pattern string in a text. It uses a rolling hash to quickly filter out positions of the text that cannot match the pattern, and then checks for a match at the remaining positions. Generalizations o
Knuth–Morris–Pratt algorithm - Wikipedia
In computer science, the Knuth–Morris–Pratt algorithm (or KMP algorithm) is a string-searching algorithm that searches for occurrences of a "word" W within a main "text string" S by employing the observation that when a mismatch occurs, the word itself embodies sufficient information to determine where the next match could begin, thus bypassing re-examination of previously matched characters. The
Aho–Corasick algorithm - Wikipedia
In computer science, the Aho–Corasick algorithm is a string-searching algorithm invented by Alfred V. Aho and Margaret J. Corasick in 1975.[1] It is a kind of dictionary-matching algorithm that locates elements of a finite set of strings (the "dictionary") within an input text. It matches all strings simultaneously. The complexity of the algorithm is linear in the length of the strings plus the le
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DPã®è©± - aizuzia
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Problem Solving with Algorithms and Data Structures using Python — Problem Solving with Algorithms and Data Structures
Problem Solving with Algorithms and Data Structures using Python¶ By Brad Miller and David Ranum, Luther College Assignments There is a wonderful collection of YouTube videos recorded by Gerry Jenkins to support all of the chapters in this text. Acknowledgements¶ We are very grateful to Franklin Beedle Publishers for allowing us to make this interactive textbook freely available. This online versi
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Marching cubes - Wikipedia
Head and cerebral structures (hidden) extracted from 150 MRI slices using marching cubes (about 150,000 triangles) Marching cubes is a computer graphics algorithm, published in the 1987 SIGGRAPH proceedings by Lorensen and Cline,[1] for extracting a polygonal mesh of an isosurface from a three-dimensional discrete scalar field (the elements of which are sometimes called voxels). The applications o
Smoothed-particle hydrodynamics - Wikipedia
Schematic view of an SPH convolution Flow around cylinder with free surface modelled with SPH. See[1] for similar simulations. Smoothed-particle hydrodynamics (SPH) is a computational method used for simulating the mechanics of continuum media, such as solid mechanics and fluid flows. It was developed by Gingold and Monaghan[2] and Lucy[3] in 1977, initially for astrophysical problems. It has been
Marching squares - Wikipedia
This article includes a list of references, related reading, or external links, but its sources remain unclear because it lacks inline citations. Please help improve this article by introducing more precise citations. (February 2022) (Learn how and when to remove this message) In computer graphics, marching squares is an algorithm that generates contours for a two-dimensional scalar field (rectang
Wikispaces
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Code Excited Linear Prediction - Wikipedia
Code Excited Linear Prediction（CELPã€ã‚»ãƒ«ãƒ—）ã¯ç·šå½¢äºˆæ¸¬ç¬¦å·ãƒ»ãƒ™ã‚¯ãƒˆãƒ«é‡å化・åˆæˆã«ã‚ˆã‚‹åˆ†æžã‚’組ã¿åˆã‚ã›ãŸéŸ³å£°ç¬¦å·åŒ–アルゴリズムã§ã‚る。直訳ã™ã‚‹ã¨ã€Œç¬¦å·åŠ±æŒ¯ç·šå½¢äºˆæ¸¬ã€ã€‚ CELPã¯å½“時ã®æ—¢å˜ã®ä½Žãƒ“ットレートã®ã‚¢ãƒ«ã‚´ãƒªã‚ºãƒ （RELPã€LPCã€ãƒ´ã‚©ã‚³ãƒ¼ãƒ€ãƒ¼ã®FS-1015ãªã©ï¼‰ã«æ¯”ã¹ã¦æ ¼æ®µã«å„ªã‚ŒãŸéŸ³è³ªã‚’示ã—ãŸã€‚様々ãªæ´¾ç”ŸãŒç”Ÿã¾ã‚Œï¼ˆACELPã€RCELPã€LD-CELPã€VSELPãªã©ï¼‰ã€ç¾åœ¨æœ€ã‚‚広ã使ã‚ã‚Œã¦ã„る音声符å·åŒ–アルゴリズムã§ã‚る。CELPã¯ã“ã®ã‚¢ãƒ«ã‚´ãƒªã‚ºãƒ ã®ã‚¯ãƒ©ã‚¹ã‚’指ã™ç”¨èªžã§ã‚ã‚Šã€ç‰¹å®šã®ã‚³ãƒ¼ãƒ‡ãƒƒã‚¯ã‚’指ã™ç”¨èªžã§ã¯ãªã„。 CELPアルゴリズムã¯æ¬¡ã®è€ƒãˆæ–¹ã«åŸºã¥ã„ã¦ã„ã‚‹: ç·šå½¢äºˆæ¸¬ç¬¦å· (LPC) ã«åŸºã¥ã音æºãƒ•ã‚£ãƒ«ã‚¿ãƒ¢ãƒ‡ãƒ« 声帯相当ã®éŸ³æº (励起信å·): 線形予測残差 声é“相当ã®ãƒ•ã‚£ãƒ«ã‚¿:　　　 線形予測フィルタ ベクトルé‡å化 (VQ) 㨠コードブッ
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How does XGBoost really work?
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