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mds:pa:start [19/09/2019 alle 07:51 (5 anni fa)]
Salvatore Ruggieri [Teaching Material] 		mds:pa:start [08/09/2021 alle 12:25 (3 anni fa)] (versione attuale)
Nicola Ciaramella [Instructor]
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-====== Programmatic Advertising A.Y. 2016/17 ======+====== Programmatic Advertising A.Y. 2019/20 ======
  
 When you submit Google (or another search engine) a request, you fire an online auction: in much less than a second, many advertisers’ algorithms launch their offers and a Google algorithm chooses the winners, which gain the right to show you their advertisements. Similar events happen when you enter a web site, a social network or an app delivering you advertisements.\\  When you submit Google (or another search engine) a request, you fire an online auction: in much less than a second, many advertisers’ algorithms launch their offers and a Google algorithm chooses the winners, which gain the right to show you their advertisements. Similar events happen when you enter a web site, a social network or an app delivering you advertisements.\\ 
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 No advanced background in mathematics or computer science is required. No advanced background in mathematics or computer science is required.
  
-Contents:\\  + 
-• Digital advertising and e-commerce: business context; programmatic vs. traditional approach; the profession of programmatic advertising; the economy of online auctions.\\  +=====Contents===== 
-• Decision-making: expected utility, optimization, heuristics.\\  + 
-• Multi-armed bandits: a conceptual framework for maximizing profit in a dynamic uncertain environment.\\  +  * Digital advertising and e-commerce: business context; programmatic vs. traditional approach; the profession of programmatic advertising; the economy of online auctions. 
-• Basic statistical tools: distributions (like Normal, Binomial, Beta); concept of simulation; Bayesian inference.\\  +  * Decision-making: expected utility, optimization, heuristics. 
-• Forecasting: regression; time series analysis; matrix-based methods.\\  +  * Multi-armed bandits: a conceptual framework for maximizing profit in a dynamic uncertain environment. 
-• Advertising and e-commerce with customer profiles available.+  * Basic statistical tools: distributions (like Normal, Binomial, Beta); concept of simulation; Bayesian inference. 
 +  * Forecasting: regression; time series analysis; matrix-based methods. 
 +  * Advertising and e-commerce with customer profiles available.
  
 =====Instructor===== =====Instructor=====
  
   * **Nicola Ciaramella**   * **Nicola Ciaramella**
-    * [[http://pages.di.unipi.it/ruggieri/]] +    * [[sidunipisa@gmail.com]]  
-    * [[ciaramella@noesis-research.com]]  +
  
 =====Teaching Material===== =====Teaching Material=====
mds/pa/start.1568879464.txt.gz · Ultima modifica: 19/09/2019 alle 07:51 (5 anni fa) da Salvatore Ruggieri

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