Algebraic Geometry and Statistical Learning Theory (Hardcover)
            
暫譯: 代數幾何與統計學習理論 (精裝版)
        
        Sumio Watanabe
- 出版商: Cambridge
- 出版日期: 2009-08-13
- 售價: $4,050
- 貴賓價: 9.5 折 $3,848
- 語言: 英文
- 頁數: 300
- 裝訂: Hardcover
- ISBN: 0521864674
- ISBN-13: 9780521864671
- 
    相關分類:
    
      機率統計學 Probability-and-statistics
 
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商品描述
      Sure to be influential, Watanabe's book lays the foundations for the use of algebraic geometry in statistical learning theory. Many models/machines are singular: mixture models, neural networks, HMMs, Bayesian networks, stochastic context-free grammars are major examples. The theory achieved here underpins accurate estimation techniques in the presence of singularities.
    
      商品描述(中文翻譯)
確實會產生影響,渡邊的書籍為代數幾何在統計學習理論中的應用奠定了基礎。許多模型/機器都是奇異的:混合模型、神經網絡、隱馬可夫模型(HMMs)、貝葉斯網絡、隨機上下文無關文法是主要的例子。這裡所達成的理論支撐了在存在奇異性時的準確估計技術。

 
     
     
     
    
 
     
    
 
     
     
    
 
    
 
     
    
 
     
     
     
     
     
     
     
     
    
 
     
     
     
     
    
 
     
     
    