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)

IMPORTANT: this is the last post I publish on this blog, because the thesis is over. You can reach me on my professional blog.

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

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