[來源請求] Tipping, Michael E. Sparse Bayesian Learning and the Relevance Vector Machine. Journal of Machine Learning Research. 2001, 1: 211–244 [2010-03-31]

机器学习

機器學習是用數據或以往的經驗，以此優化計算機程序的性能標準。另外，電腦科學家湯姆·米切爾（英语：Tom M. Mitchell）在其著作的Machine Learning一書中定義的機器學習為： A computer program is said to learn from experience E with

量子機器學習

Sinayskiy, Ilya; Petruccione, Francesco. An introduction to quantum machine learning. Contemporary Physics. 2014, 56 (2): 172–185. Bibcode:2015ConPh..56

提升方法

manuscript (Machine Learning class project, December 1988) Schapire, Robert E. The Strength of Weak Learnability (PDF). Machine Learning. 1990, 5 (2):

归纳偏置

biases in machine learning （页面存档备份，存于互联网档案馆）. Machine Learning Journal, 5:1--17, 1995. Mitchell, T.M. (1980). The need for biases in learning generalizations

Found in articles

相关向量机

[來源請求] Tipping, Michael E. Sparse Bayesian Learning and the Relevance Vector Machine. Journal of Machine Learning Research. 2001, 1: 211–244 [2010-03-31]

机器学习

量子機器學習

Sinayskiy, Ilya; Petruccione, Francesco. An introduction to quantum machine learning. Contemporary Physics. 2014, 56 (2): 172–185. Bibcode:2015ConPh..56

提升方法

manuscript (Machine Learning class project, December 1988) Schapire, Robert E. The Strength of Weak Learnability (PDF). Machine Learning. 1990, 5 (2):

归纳偏置

biases in machine learning （页面存档备份，存于互联网档案馆）. Machine Learning Journal, 5:1--17, 1995. Mitchell, T.M. (1980). The need for biases in learning generalizations