ã¡ãã£ã¨æ©æ¢°å¦ç¿ã®æ¯è¼çæåãªã¢ãã«ãã¢ã«ã´ãªãºã ã®ååºã«ã¤ãã¦å¹´è¡¨ãä½ã£ã¦ã¿ãã
ã£ã¦今週末用の資料ãªãã ãã©ãï½
1805 | Method of Least Squares |
1901 | PCA (Principal Component Analysis) |
1905 | Random Walk |
-1925 | Logistic Regression |
1936 | Fisher's Linear Discriminant Analysis |
1946 | Monte Carlo Method |
1948 | n-gram model |
1950 | RKHS (Reproducing Kernel Hilbert Space) |
1950s | Markov Decision Process |
-1957 | Perceptron |
1958 | Kalman Filter |
1960s | Hidden Markov Model |
-1961 | Neural Network (Multi-Layer Perceptron) |
1962 | L2 regularity |
1967 | Viterbi Algorithm |
-1970 | Metropolis-Hastings algorithm |
1973 | Dirichlet Process |
1975 | Mean Shirt Clustering |
1977 | EM Algorithm |
1980 | Graphical Modeling |
1982 | SOM (Self-Organizing Map) |
-1984 | Gibbs sampling |
1984 | CART (Classification And Regression Tree) |
1984 | PAC learning |
1984 | Markov Random Field |
1985 | Bayesian Network |
1988 | Variational Bayesian method |
1989 | Graph Cut |
1994 | L1 regularity |
1994 | ICA (Independent Component Analysis) |
1995 | Support Vector Machine |
1995 | AdaBoost |
1995 | Particle Filter |
1999 | LSH (Locality Sensitive Hashing) |
2000 | FP-Growth |
2001 | Item-based Collaborative Filtering |
2001 | Random Forest |
2001 | CRF (Conditional Random Field) |
2001 | Expectation Propagation |
2003 | Slice sampling |
2003 | LDA (Latent Dirichlet Allocation) |
ã¡ãªã¿ã« Logistic Regression 㯠19ä¸ç´ä¸é ã« logistic é¢æ°ã®ãçºè¦ãã1920 å¹´ã«ä»ã® Logistic Regression ç¸å½ãåºããã©ã¾ã ãã®ååã§ãªãããã®å¾ logistic é¢æ°ã®ãåçºè¦ããçµã¦ã1925 å¹´ã«ãã§ãã Logistic Regression ã¨ãªãã¾ãããã¨ããçµç·¯ã£ã½ãã
Linear Regression 㯠19ä¸ç´åé ãããããå§ã¾ãã1920 年代㫠Fisher ã®æã«ãã£ã¦ã»ã¼ä»ã®å½¢ã«ãªã£ãã£ã½ããã ãã©ãã¾ããããã«è¼ããªãã¦ããããªãã¨ã
LDA ã¾ã§ãªã®ã¯ã¡ããæå³çãã¾ããã以éã¯è©ä¾¡ãå®ã¾ãã®ãããããã§ãããããã
ééããããªãã§ÃÃããªãã®ï¼ãããã®ä»ããã°ãæææè¿ã
- SOM ãå¿ãã¦ãã®ã§è¿½å ã
- Multi-layer perceptron 㨠PCA ã®å¹´ä»£ãä¿®æ£ãPerceptron 㨠Fisher's LDA ã追å (thanks to Mathieu ãã)
- MH-algorithm, Gibbs sampling, Slice sampling ã追å
- ãã£ã¨ Random walk å¿ãã¦ãâ¦â¦
- Kalman filter ã®å¹´ä»£ã 1958 ã«ä¿®æ£ãMH-algorithm & Gibbs sampling ã -1970 ã¨ãã£ã表è¨ã«(thanks to ãã¾ãã¾å ç)
- æå°äºä¹æ³è¿½å (thanks to Mathieu ãã, ãã¾ãã¾å ç)
- ã°ã©ãã£ã«ã«ã¢ãã«ããã¤ã¸ã¢ã³ãããããã«ã³ãä¹±æ°å ´ã追å (thanks to tsubosaka ããã_akisato ãã)
- ãã¼ã»ãããã³ããã¥ã¼ã©ã«ãããã¯ã¼ã¯ã®å¹´ä»£ã -1957 ã¨ãã表è¨ã«(thanks to ãã¾ãã¾å ç)
- particle filter ã®å¹´ä»£ã 1995 ã«ä¿®æ£(thanks to _akisato ãã)
- Expectation Propagation ã追å (thanks to daichi ãã)
- åçæ ¸ãã«ãã«ã空éã追å
- å¤åãã¤ãºãã mean-field theory ã®è¨è¿°ãåé¤(thanks to _akisato ãã)
- n-gram 追å