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è¿‘ä¼¼æœ€è¿‘å‚æŽ¢ç´¢Indexã‚’ä½œã‚‹ãƒ¯ãƒ¼ã‚¯ãƒ•ãƒãƒ¼ - ZOZO TECH BLOG
ã¯ã˜ã‚ã« ã“ã‚“ã«ã¡ã¯ã€‚ZOZOç ”ç©¶æ‰€ã®shikajiroã§ã™ã€‚ä¸»ã«ç ”ç©¶æ‰€ã®ãƒãƒƒã‚¯ã‚¨ãƒ³ãƒ‰å…¨èˆ¬ã‚’æ‹…å½“ã—ã¦ã„ã¾ã™ã€‚ZOZOã§ã¯2019å¹´å¤ã«AI æŠ€è¡“ã‚’æ´»ç”¨ã—ãŸã€Œé¡žä¼¼ã‚¢ã‚¤ãƒ†ãƒ æ¤œç´¢æ©Ÿèƒ½ã€ã‚’ãƒªãƒªãƒ¼ã‚¹ã—ã¾ã—ãŸã€‚å•†å“ç”»åƒã«ä¼¼ãŸåˆ¥ã®å•†å“ã‚’æ¤œç´¢ã™ã‚‹æ©Ÿèƒ½ã§ã€ ç”»åƒæ¤œç´¢ ã¨è¨€ã£ãŸæ–¹ãŒåˆ†ã‹ã‚Šã‚„ã™ã„ã‹ã‚‚ã—ã‚Œã¾ã›ã‚“ã€‚MLã®é–‹ç™ºã«ã¯Chainer, CuPy, TensorFlow, GPU, TPU, Annoyã€ãƒãƒƒã‚¯ã‚¨ãƒ³ãƒ‰ã®é–‹ç™ºã«ã¯GCP, Kubernetes, Docker, Flask, Terraform, Airflowãªã©æ§˜ã€…ãªæŠ€è¡“ã‚’æ´»ç”¨ã—ã¦ã„ã¾ã™ã€‚ä»Šå›žã¯ç§ãŒæ‹…å½“ã—ãŸã€Œè¿‘ä¼¼æœ€è¿‘å‚æŽ¢ç´¢Indexã‚’ä½œã‚‹ãƒ¯ãƒ¼ã‚¯ãƒ•ãƒãƒ¼ã€ã®ãŠè©±ã§ã™ã€‚ corp.zozo.com ç›®æ¬¡ ã¯ã˜ã‚ã« ç›®æ¬¡ ç”»åƒæ¤œç´¢ã®å…¨ä½“åƒèª¬æ˜Ž Workflow Develop Application æŽ¨è«–APIã®æµã‚Œ è¿‘ä¼¼æœ€è¿‘å‚æŽ¢ç´¢ã¨Annoy è¿‘ä¼¼
petite_blue 2020/06/11
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MIRU 2019 ãƒãƒ¥ãƒ¼ãƒˆãƒªã‚¢ãƒ«ã€€http://cvim.ipsj.or.jp/MIRU2019/index.php?id=tutorial æ¾äº• å‹‡ä½‘ï¼ˆæ±äº¬å¤§å¦ç”Ÿç”£æŠ€è¡“ç ”ç©¶æ‰€ï¼‰http://yusukematsui.me/index_jp.html ãƒ™ã‚¯ãƒˆãƒ«ã®é›†åˆã‚’å‰ã«ã—ã¦æ–°ãŸã«ã‚¯ã‚¨ãƒªãƒ™â€¦
petite_blue 2019/07/29
nns

algorithm
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petite_blue 2017/07/01
Approximate Nearest Neighbor Search on High Dimensional Data â€” Experiments, Analyses, and Improvement

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GitHub - DBAIWangGroup/nns_benchmark: Benchmark of Nearest Neighbor Search on High Dimensional Data
petite_blue 2017/07/01
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èˆˆå‘³æ·±ã„ãƒ‡ãƒ¼ã‚¿æ§‹é€ ï¼šBKæœ¨ | POSTD
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petite_blue 2017/07/01
bk-tree

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BK-tree ã‚’ golang ã§å®Ÿè£…ã—ãŸ - å³ä¸Šâ†—
å…ˆæ—¥ã¯ã¦ã¶ã« èˆˆå‘³æ·±ã„ãƒ‡ãƒ¼ã‚¿æ§‹é€ ï¼šBKæœ¨ | ãƒ—ãƒã‚°ãƒ©ãƒŸãƒ³ã‚° | POSTD ã¨ã„ã†ç¿»è¨³è¨˜äº‹ ( å…ƒè¨˜äº‹ http://signal-to-noise.xyz/post/bk-tree/) ãŒã‚ãŒã£ã¦ã„ã‚‹ã®ã‚’ã¿ã¦åˆã‚ã¦ BK-tree ã¨ã„ã†ã‚‚ã®ã‚’çŸ¥ã£ãŸã®ã§ï¼Œgolang ã§å®Ÿè£…ã—ã¦ã¿ã¾ã—ãŸï¼Ž github.com BK-tree ã¨ã¯ å…ˆç¨‹ã®è¨˜äº‹ã«å…¨éƒ¨æ›¸ã„ã¦ã‚ã‚‹ã®ã§ã™ãŒâ€¦ BK-tree ã¯ï¼Œã‚ã‚‹è·é›¢ç©ºé–“å†…ã§è¿‘å‚ç‚¹æŽ¢ç´¢ã‚’åŠ¹çŽ‡çš„ã«è¡Œãˆã‚‹ãƒ‡ãƒ¼ã‚¿æ§‹é€ ã§ã™ï¼Žåˆ©ç”¨ä¾‹ã¨ã—ã¦ã¯ã‚¹ãƒšãƒ«ãƒã‚§ãƒƒã‚¯ã‚„é¡žä¼¼ç”»åƒæ¤œç´¢ãªã©ãŒã‚ã‚Šã¾ã™ï¼Ž è·é›¢ç©ºé–“ã¨ã¯ï¼Œãªã«ã‹ã—ã‚‰ã®è·é›¢ã‚’è¨ˆç®—ã™ã‚‹ã“ã¨ãŒã§ãã‚‹ç©ºé–“ã®ã“ã¨ã§ï¼Œè·é›¢ã¨ã—ã¦ãƒãƒŸãƒ³ã‚°è·é›¢ã‚„ãƒžãƒ³ãƒãƒƒã‚¿ãƒ³è·é›¢ï¼Œãƒ¬ãƒ¼ãƒ™ãƒ³ã‚·ãƒ¥ã‚¿ã‚¤ãƒ³è·é›¢ï¼Œãƒ¦ãƒ¼ã‚¯ãƒªãƒƒãƒ‰è·é›¢ãªã©ãªã©ãŒæŒ™ã’ã‚‰ã‚Œã¾ã™ï¼Ž ä¾‹ãˆã°ï¼Œã„ã‚ã‚†ã‚‹æ™®é€šã® 3 æ¬¡å…ƒã®ç©ºé–“ã¯ï¼Œãƒ¦ãƒ¼ã‚¯ãƒªãƒƒãƒ‰è·é›¢ã‚’è·é›¢é–¢æ•°ã«æŒã¤è·é›¢ç©ºé–“ã¨è€ƒãˆã‚‰ã‚Œã¾ã™ï¼Ž è¿‘å‚ç‚¹æŽ¢ç´¢
petite_blue 2017/07/01
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ä¹±æŠžãƒ‡ãƒ¼ã‚¿æ§‹é€ ã®æœ€æ–°äº‹æƒ… ï¼MinHash ã¨ HyperLogLog ã®æœ€è¿‘ã®é€²æ©ï¼
MinHash, b-bit MinHash, HyperLogLog, Odd Sketch, HIP Estimator ã®è§£èª¬ã§ã™ï¼ŽRead less
petite_blue 2017/06/30
nns

minhash
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Locality-sensitive hashing - Elasticsearch
petite_blue 2017/06/30
nns
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Johnsonâ€“Lindenstrauss lemma - Wikipedia
In mathematics, the Johnsonâ€“Lindenstrauss lemma is a result named after William B. Johnson and Joram Lindenstrauss concerning low-distortion embeddings of points from high-dimensional into low-dimensional Euclidean space. The lemma states that a set of points in a high-dimensional space can be embedded into a space of much lower dimension in such a way that distances between the points are nearly
petite_blue 2017/06/30
math

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MinHashã«ã‚ˆã‚‹é«˜é€Ÿãªé¡žä¼¼æ¤œç´¢ - Preferred Networks Research & Development
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petite_blue 2012/07/21
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