Machine Learning

Presentation Information and Schedule

Proposal due November 15, 2010

On or before the above due date you should email me (holder@wsu.edu) an electronic copy or URL of the paper for your class presentation. Also, include date preferences for your presentation (see below for possible presentation dates). The paper should be from a recent (no more than 3 years old) conference related to machine learning, such as

• International Conference on Machine Learning (ICML)
• International Conference on Knowledge Discovery and Data Mining (KDD)
• SIAM Data Mining Conference (SDM)
• IEEE International Conference on Data Mining (ICDM)
• National Conference on Artificial Intelligence (AAAI)
• International Joint Conference on Artificial Intelligence (IJCAI)

Tips for Good Presentations

• Since you don't have much time, and you will be graded on your coverage of the material, use some form of electronic delivery (e.g., PowerPoint).
• Do not put too much text per slide and use big fonts.
• Do not read your slides. Face the audience and paraphrase the ideas on the slides, using the slide bullets at reminders.
• Use graphics and multimedia effectively to help make your points, but not just for flash.
• Know everything you present. Be able to explain in detail any aspect of the information you present.

Presentation Grading

• Presentation quality and delivery
• Coverage of topic
• Knowledge of topic
• Critical evaluation of topic

Number	Presenter	Paper
1	Grigoleit	S. Bickel et al. (2007). Discriminative Learning for Differing Training and Test Distributions. Proceedings of the 24th International Conference on Machine Learning (ICML). Corvallis, Oregon.
2	Ray	F. Provost et al. (2009). Frequent Pattern Mining with Uncertain Data. Fifteenth ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). Paris, France.

Number	Presenter	Paper
1	Narasimhan	J. Vanschoren et al. (2008) Learning from the Past with Experiment Databases. Tenth Pacific Rim International Conference on Artificial intelligence: Trends in Artificial Intelligence (Hanoi, Vietnam, December 15-19, 2008). T. Ho and Z. Zhou, Eds. Lecture Notes In Artificial Intelligence, vol. 5351. Springer-Verlag, Berlin, Heidelberg, 485-496.
2	Rytsareva	F. Mascia et al. (2010). Predicting Structural and Functional Sites in Proteins by Searching for Maximum-Weight Cliques. Twenty-Fourth AAAI Conference on Artificial Intelligence. Atlanta, Georgia.

Number	Presenter	Paper
1	Kamath	K. Das and J. Schneider (2007). Detecting Anomalous Records in Categorical Datasets. Thirteenth ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). San Jose, CA.
2	Guo	R. Raina et al. (2007). Self-taught Learning: Transfer Learning from Unlabeled Data. Proceedings of the 24th International Confer- ence on Machine Learning (ICML), Corvallis, OR.

Number	Presenter	Paper
1	Wang	F. Provost et al. (2009). Audience Selection for On-line Brand Advertising: Privacy-friendly Social Network Targeting. Fifteenth ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). Paris, France.
2	Liu	T. Huynh et al. (2008). Discovery of Activity Patterns using Topic Models. Tenth International Conference on Ubiquitous Computing (UbiComp). Seoul, South Korea.

Number	Presenter	Paper
1	Dawadi	S. Gupta et al. (2009). Catching the Drift: Learning Broad Matches from Clickthrough Data. Fifteenth ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). Paris, France.
2	Akter	J. Chang et al. (2009). Connections between the Lines: Augmenting Social Networks with Text. Fifteenth ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). Paris, France.