2011 Group Project2 Goal: Groups of 3 students (preferred, 2 and 4 is also okay; students pick a topic, work 3 weeks on the topic, and prepare a 5-8-page report (or webpage) and give a minute presentation. Has to be something with machine learning A project you are interested in works better Using software packages OK, particularly comparing tools and algorithms is fine Reviewing and comparing 2 papers that present different algorithm/approaches for the same problems is fine Applications of Machine Learning is fine Theory problem OK Project ends: April 16/18, 2011 (Student presentations: April 14+19)

Example Project Themes Finding scene lighting from face images Predicting Musical Scores Use of machine learning in urban driving Customer and product clustering for recommender systems Comparing Naïve Bayes and Neural nets for text classification Adaptation in a virtual animal world using reinforcement learning Predicting success of major league baseball teams Differences between ML and MAP estimators Compare algorithm X and Y Paper review and comparison Predicting the future success/failure of graduate students Survey on Multi-dimensional scaling techniques and tools Remark: Projects that do programming/use ML-tools are fine, but other projects are equally welcome.

Other Comments Project2 Report should have 4-6 pages for groups of size 2, 5-7 pages for groups of size 3, single spaced with an 11-point or 12-point font (if you have other deliverables instead, discuss it with Chun-sheng); if you produces something else during the project (e.g. a program) submit it as an appendix. Follow the traditional organization when writing the report: short abstract, introduction, main part (can be several sections), conclusion, references. Reference all sources you used in your final report including your own publications (  not doing so is cheating!!!) Groups of 2 give a minute presentation and larger groups give a minute presentation. Each group member should participate in the presentation. Practice your presentation; make sure you stay within the time limits. Introduce your topic clearly; be aware of the fact that students in the course might not know much about the topic you are working on. Quality of presentations counts 30% towards the overall grade.