Machine Learning

Presentation Information and Schedule

Proposal due November 16, 2009

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	Seth Long	V. Garcia, E. Debreuve and M. Barlaud (2008). Fast k Nearest Neighbor Search using GPU. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshop.
2	Eric Wang	L. Li, M. Littman and T. Walshi (2008). Knows What It Knows: A Framework For Self-Aware Learning. Proceedings of the 25th International Conference on Machine Learning.
3	Aaron Crandall	S. Risi, S. Vanderbleek, C. Hughes and K. Stanley (2009). How Novelty Search Escapes the Deceptive Trap of Learning to Learn. Proceedings of the Genetic and Evolutionary Computation Conference.

Number	Presenter	Paper
1	Gokcen Cilingir	J. Zeng, R. Alhajj and D. Demetrick (2009). Adaptive Multi-agent Architecture for Functional Sequence Motifs Recognition. Bioinformatics.
2	Joel Helkey	J. Gao, W. Fan and J. Han (2007). On Appropriate Assumptions to Mine Data Streams: Analysis and Practice. Proceedings of the Seventh IEEE International Conference on Data Mining.
3	Cewei Cui	L. Xu, M. White and D. Schuurmans (2009). Optimal Reverse Prediction: A Unified Perspective on Supervised, Unsupervised and Semi-supervised Learning. Proceedings of the 26th International Conference on Machine Learning.

Number	Presenter	Paper
1	Richard Lee	C. Bustamante, L. Garrido and R. Soto (2006). Fuzzy Naive Bayesian Classification in RoboSoccer 3D: A Hybrid Approach to Decision Making. Proceedings of the RoboCup International Conference.
2	Yunyun Zhou	S. Mohamed, D. Rubin and T. Marwala (2007). Incremental Learning for Classification of Protein Sequences. Proceedings of International Joint Conference on Neural Networks.
3	Raghavendiran Srinivasan	A. Crandall and D. Cook (2008). Attributing events to individuals in multi-inhabitant environments. Proceedings of the International Conference on Intelligent Environments.

Number	Presenter	Paper
1	Yasamin Sahaf	G. Singla, D. Cook and M. Schmitter-Edgecombe (2009). Tracking Activities in Complex Settings Using Smart Environment Technologies. International Journal of BioSciences, Psychiatry and Technology, 1(1):25-35.
2	Roben Tan	J. Gao, G. Agrawal, J. Thelen, Z. Obradovic, A. Dunker and D. Xu (2009). A New Machine Learning Approach for Protein Phosphorylation Site Prediction in Plants, Proceedings of the First International Conference on Bioinformatics and Computional Biology.
3	Muksitul Haque	Y. Zhang, A. Surendran, J. Platt and M. Narasimhan (2008). Learning from Multitopic Web Documents for Contextual Advertisement. Proceedings of the International Conference on Knowledge Discovery and Data Mining (KDD)

Number	Presenter	Paper
1	Ehsan Nazerfard	K. Fujimoto and S. Nakabayashi (2003). Applying GMDH Algorithm to Extract Rules from Examples. Systems Analysis Modelling Simulation, 43(10):1311-1319.
2	Barnan Das	D. Riedel, S. Venkatesh and W. Liu (2005). Spatial Activity Recognition in a Smart Home Environment using a Chemotactic Model. Proceedings of the International Conference on Intelligent Sensors, Sensor Networks and Information Processing.
3	Bolong Zeng	C. Elkan and K. Noto (2008). Learning Classifiers from Only Positive and Unlabeled Data. Proceedings of the International Conference on Knowledge Discovery and Data Mining (KDD).

Number	Presenter	Paper
1	Zachary Wemlinger	R. Salakhutdinov, A. Mnih and G. Hinton (2007). Restricted Boltzmann Machines for Collaborative Filtering. Proceedings of the 24th International Conference on Machine Learning.
2	Svetlana Lockwood	Y. Ye, T. Li, Q. Jiang, Z. Han and L. Wan (2009). Intelligent File Scoring System for Malware Detection from the Gray List. Proceedings of the International Conference on Knowledge Discovery and Data Mining (KDD).
3	Brian Thomas	D. Patnaik, M. Marwah, R. Sharma and N. Ramakrishnan (2009). Sustainable Operation and Management of Data Center Chillers using Temporal Data Mining. Proceedings of the International Conference on Knowledge Discovery and Data Mining (KDD).