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magistraleinformatica:aa2:start [07/05/2015 alle 11:37 (9 anni fa)]
Davide Bacciu [Lectures] 		magistraleinformatica:aa2:start [04/04/2016 alle 10:20 (8 anni fa)] (versione attuale)
Davide Bacciu Communication on course replacement for year 2015/2016
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 ===== News ===== ===== News =====
  
-**(02/04/2015)** List of midterm assignments to students is now out +**(04/04/2016) Note for Students of Academic Year 2015/2016**  The AA2 course is **inactive** during year 2015/2016. Students interested in the course can take the replacement course [[http://didawiki.di.unipi.it/doku.php/bionics-engineering/computational-neuroscience/start|"Computational Neuroscience"]] from the M.Sc. in Bionics Engineering.  
 + 
 +(02/04/2015) List of midterm assignments to students is now out 
  
 (13/03/2015) Midterm reading list and dates now out  (13/03/2015) Midterm reading list and dates now out 
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 | 16 | 27/4/15 (11-13) | C1 | Deep Learning {{:magistraleinformatica:aa2:generative-7-hand.pdf| slides}}| [[magistraleinformatica:aa2:start#further_readings|[18]]] A classic divulgative paper from the initiator of Deep Learning \\ [[magistraleinformatica:aa2:start#further_readings|[19]]] Recent review paper \\ | [[magistraleinformatica:aa2:start#further_readings|[20]]] A freely available book on deep learning from Microsoft RC | | 16 | 27/4/15 (11-13) | C1 | Deep Learning {{:magistraleinformatica:aa2:generative-7-hand.pdf| slides}}| [[magistraleinformatica:aa2:start#further_readings|[18]]] A classic divulgative paper from the initiator of Deep Learning \\ [[magistraleinformatica:aa2:start#further_readings|[19]]] Recent review paper \\ | [[magistraleinformatica:aa2:start#further_readings|[20]]] A freely available book on deep learning from Microsoft RC |
 | 17 | 30/4/15 (14-16) | C1 | Kernel and non-parametric methods: kernel method refresher; kernels for complex data (sequences, trees and graphs); convolutional kernels; adaptive kernels {{:magistraleinformatica:aa2:kernel-1-hand.pdf| slides}} | [KM] Chapters 2 and 9 - Kernel  methods refresher and kernel construction \\ [KM] Chapter 11 - Kernels for structured data \\ [KM] Chapter 12 - Generative kernels | [[magistraleinformatica:aa2:start#further_readings|[21]]] Generative kernels on hidden states multisets | | 17 | 30/4/15 (14-16) | C1 | Kernel and non-parametric methods: kernel method refresher; kernels for complex data (sequences, trees and graphs); convolutional kernels; adaptive kernels {{:magistraleinformatica:aa2:kernel-1-hand.pdf| slides}} | [KM] Chapters 2 and 9 - Kernel  methods refresher and kernel construction \\ [KM] Chapter 11 - Kernels for structured data \\ [KM] Chapter 12 - Generative kernels | [[magistraleinformatica:aa2:start#further_readings|[21]]] Generative kernels on hidden states multisets |
-| 18 | 04/5/15 (11-13) | C1 | Kernel and non-parametric methods: Linear and Non-Linear Dimensionality Reduction (guest lecture by [[http://ekvv.uni-bielefeld.de/pers_publ/publ/PersonDetail.jsp?personId=34943216&lang=en|Alexander Schulz]]) {{:magistraleinformatica:aa2:linear_and_nonlinear_dr.pdf| slides}} | [BRML] Sect. 15.1-15.2 PCA \\ [BRML] Sect. 15.7 Kernel PCA | [[magistraleinformatica:aa2:start#further_readings|[22]]] t-SNE | +| 18 | 04/5/15 (11-13) | C1 | Kernel and non-parametric methods: Linear and Non-Linear Dimensionality Reduction (guest lecture by [[http://ekvv.uni-bielefeld.de/pers_publ/publ/PersonDetail.jsp?personId=34943216&lang=en|Alexander Schulz]]) {{:magistraleinformatica:aa2:linearandnonlineardr.pdf| slides}} | [BRML] Sect. 15.1-15.2 PCA \\ [BRML] Sect. 15.7 Kernel PCA | [[magistraleinformatica:aa2:start#further_readings|[22]]] t-SNE | 
-| 19 | 07/5/15 (14-16) | C1 | Kernel and non-parametric methods: Recent Advances in Dimensionality Reduction (guest lecture by [[http://ekvv.uni-bielefeld.de/pers_publ/publ/PersonDetail.jsp?personId=34943216&lang=en|Alexander Schulz]]) |  |  |+| 19 | 07/5/15 (14-16) | C1 | Kernel and non-parametric methods: Recent Advances in Dimensionality Reduction (guest lecture by [[http://ekvv.uni-bielefeld.de/pers_publ/publ/PersonDetail.jsp?personId=34943216&lang=en|Alexander Schulz]]) {{:magistraleinformatica:aa2:linearandnonlineardr.pdf| slides}} |  |  |
 | 20 | 11/5/15 (11-13) | C1 | An Overview of ML research at UNIPI; final project proposals |  |  | | 20 | 11/5/15 (11-13) | C1 | An Overview of ML research at UNIPI; final project proposals |  |  |
 +| 21 | 18/5/15 (11-13) | C1 | Company Talk: [[http://www.henesis.eu/|Henesis]] (Artificial Perception) |  |  |
 +| 22 | 21/5/15 (14-16) | C1 | Company Talk: [[http://kode-solutions.net/|Kode]] Solutions |  |  |
 +| 23 | 21/5/15 (16-18) | C1 | Final lecture: course wrap-up; final project assignments; exam information |  |  |
 ===== Exams ===== ===== Exams =====
  
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 Students must select the project type and topic before the last lecture of the course. The project report/software should be handled (at least) 7 days before its [[magistraleinformatica:aa2:start#oral_presentation|oral presentation]].  Students must select the project type and topic before the last lecture of the course. The project report/software should be handled (at least) 7 days before its [[magistraleinformatica:aa2:start#oral_presentation|oral presentation]]. 
 +
 +**NEW!!** Project reports should be formatted using the provided {{:magistraleinformatica:aa2:final-report-tex.zip|LaTex}} or {{:magistraleinformatica:aa2:final-report.doc|MS Word}} templates.  
  
 ==== Oral Presentation ====  ==== Oral Presentation ==== 
magistraleinformatica/aa2/start.1430998678.txt.gz · Ultima modifica: 07/05/2015 alle 11:37 (9 anni fa) da Davide Bacciu

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