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magistraleinformatica:aa2:start [30/04/2015 alle 15:00 (9 anni fa)] Davide Bacciu [Lectures] Upload slides lecture 17 |
magistraleinformatica:aa2:start [11/06/2015 alle 15:22 (9 anni fa)] Davide Bacciu [Lectures] |
| 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]]) | | | | | 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 | | | |
| | 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]]. |
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| **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. |
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==== Oral Presentation ==== | ==== Oral Presentation ==== |
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[[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6889768&tag=1|[21]]] D. Bacciu, A. Micheli and A. Sperduti, Integrating Bi-directional Contexts in a Generative Kernel for Trees, Proceedings of the 2014 IEEE International Joint Conference on Neural Networks (IJCNN'14), pp.4145 - 4151, IEEE, 2014 | [[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6889768&tag=1|[21]]] D. Bacciu, A. Micheli and A. Sperduti, Integrating Bi-directional Contexts in a Generative Kernel for Trees, Proceedings of the 2014 IEEE International Joint Conference on Neural Networks (IJCNN'14), pp.4145 - 4151, IEEE, 2014 |
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| [[http://www.jmlr.org/papers/volume9/vandermaaten08a/vandermaaten08a.pdf|[22]]] L. van der Maaten, G. Hinton, Visualizing Data using t-SNE, Journal of Machine Learning Research, Vol. 9, pp. 2579-2605, 2008 |
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