This post comes after a few months in oder to put in evidence the links to download both the thesis and the final talk.

• Download the Master’s Thesis (only in English)
• Download the final talk (ENG|ITA)

Master degree received.
Final mark: 110/110 Cum Laude.

A definitive draft of the final talk (it is in Italian language) is available for download

Download Compressed (bzip2) PDF (4.7MB)

Download PDF (6.8MB)

The final draft of the thesis is available for download here.

Final contents are:

• Chapter 1: Introduction
• Chapter 2: Machine learning essentials
• Chapter 3: Clustering and related issues
• Chapter 4: Previous works on clustering
• Chapter 5: Minimum Bregman Information principle for Co-clustering
• Chapter 6: Support Vector Clustering
• Chapter 7: Alternative Support Vector Methods for Clustering
• Chapter 8: Support Vector Clustering software development
• Chapter 9: Experiments
• Chapter 10: Conclusion and Future Work
• Appendix A: One Class classification via Support Vector Machines
• Appendix B: Resource usage of the algorithms
• Appendix C: Star/Galaxy separation via Support Vector Machines
• Appendix D: Thesis Web Log
• Bibliography

IMPORTANT: the file name is changed, the links in the previous posts are broken. Download the thesis from this post or from the Documents page.

Downloads

Changelog download - Thesis download

RC2 draft of the thesis. Contents are completed and read by the supervisor, prof. Anna Corazza.

Downloads

Changelog download - Thesis download

RC1 draft of the thesis. Contents are

• Chapter 1: Introduction
• Chapter 2: Machine learning essentials
• Chapter 3: Clustering and related issues
• Chapter 4: Previous works on clustering
• Chapter 5: Minimum Bregman Information principle for Co-clustering
• Chapter 6: Support Vector Clustering
• Chapter 7: Alternative Support Vector Methods for Clustering
• Chapter 8: Support Vector Clustering software development
• Chapter 9: Experiments (only overall conclusion missing)
• Chapter 10: Conclusion and Future Work
• Appendix A: One Class classification via Support Vector Machines
• Appendix B: Resources usage of the algorithms
• Appendix C: Star/Galaxy separation via Support Vector Machines
• Appendix D: Thesis Web Log
• Bibliography

Downloads

Changelog download - Thesis download

Pre-final draft of thesis. Contents are (in bold new contents and updated ones)

• Chapter 1: Introduction
• Chapter 2: Machine learning essentials
• Chapter 3: Clustering and related issues
• Chapter 4: Previous works on clustering
• Chapter 5: Minimum Bregman Information principle for Co-clustering
• Chapter 6: Support Vector Clustering
• Chapter 7: Alternative Support Vector Methods for Clustering
• Chapter 8: Support Vector Clustering software development
• Chapter 9: Experiments (Incomplete, Text Clustering results missing)
• Chapter 10: Conclusion and Future Work
• Appendix A: One Class classification via Support Vector Machines
• Appendix B: Resources usage of the algorithms
• Appendix C: Star/Galaxy separation via Support Vector Machines
• Appendix D: Thesis Web Log
• Bibliography

Downloads

Changelog download - Thesis download

Eight draft of thesis. Contents are (in bold new contents)

• Chapter 1: Introduction
• Chapter 2: Machine learning essentials
• Chapter 3: Clustering and related issues
• Chapter 4: Previous works on clustering
• Chapter 5: Minimum Bregman Information principle for Co-clustering
• Chapter 6: Support Vector Clustering
• Chapter 7: Alternative Support Vector Methods for Clustering
• Chapter 8: Support Vector Clustering software development
• Chapter 9: Experiments (Incomplete, only two experimental stages out of 5)
• Chapter 10: Conclusion and Future Work
• Appendix A: One Class classification via Support Vector Machines
• Appendix B: Resources usage of the algorithms
• Appendix C: Thesis Web Log
• Bibliography

Downloads

Changelog download - Thesis download

Seventh draft of thesis. Contents are (in bold new contents)

• Chapter 1: Introduction
• Chapter 2: Machine learning essentials
• Chapter 3: Clustering and related issues
• Chapter 4: Previous works on clustering
• Chapter 5: Minimum Bregman Information principle for Co-clustering
• Chapter 6: Support Vector Clustering
• Chapter 7: Alternative Support Vector Methods for Clustering
• Chapter 8: Support Vector Clustering software development
• Chapter 9: Experiments (Incomplete, only two experimental stages out of 5)
• Chapter 10: Conclusion and Future Work
• Appendix A: One Class classification via Support Vector Machines
• Appendix B: Time and space consume (to be completed)
• Appendix C: Thesis Web Log
• Bibliography

Downloads

Changelog download - Thesis download

Sixth draft of thesis. Contents are (in bold new contents)

• Chapter 1: Introduction
• Chapter 2: Machine learning essentials
• Chapter 3: Clustering and related issues
• Chapter 4: Previous works on clustering
• Chapter 5: Minimum Bregman Information principle for Co-clustering
• Chapter 6: Support Vector Clustering
• Chapter 7: Alternative Support Vector Methods for Clustering
• Chapter 9: Support Vector Clustering software development
• Chapter 10: Conclusion and Future Work
• Appendix A: One Class classification via Support Vector Machines
• Appendix B: Thesis Web Log
• Bibliography

Downloads

Changelog download - Thesis download