EECS 545: Machine Learning: Projects, Fall 2011

• Classification of Tweets via Clutering of Hashtags, Dolan Antenucci, Gregory Handy, Akshay Modi and Miller Tinkerhess
• Algorithms for Completing a User Ratings Matrix, Nick Asendorf, Madison McGaffin, Matt Prelee and Ben Schwartz
  • Voted best poster by the class
• Learning Finite Empirical Games, Paolo Bianchi, Ben Cassell and Elaine Wah
• Text Super-Resolution and Deblurring using Multiple Support Vector Regression, Roy Blankman, Sean McMillan and Ross Smith
• Location Recognition Combining In/Outdoor Classification and Boosted Classifiers, Yu-Hui Chen, Bing Liao, Ko-Tung Lin and Yi-Husan Tsai
• Predicting Seizures Using Spectral Clustering and Cost-Sensitive SVM's, Xiyu Duan, Chris Fink, Hao Sun and Tianpei Xie
• Transfer Learning based on Optimal Reward, Monica Eboli, Weihong Guo, Nan Jiang and Sean Newman
• Multiple Instance Learning for Drug Activity Prediction, Ridvan Eksi, Aria Ghasemian Sahebi and Raj Tejas Suryaprakash
• Classification of Brain States from fMRI Data Using Machine Learning Techniques, Ashish Farmer, Yash Shah and Haixuan Sun
• Embedding based Regression in Nonlinear System, Vijay Manikandan Janakiraman, Dae Yon Jung, Donghwan Kim and Kihyuk Sohn
• Experiments in Automatic Text Summarization Using Deep Neural Networks, Rahul Jha, Tyler Johnson, Ben King and Vaishnavi Sundararajan
• Querying Methods for Twitter using Topic Modeling, Yang Liu, Eric Uthoff, Robert Vandermeulen and Lei Yang
• Learning Loop Closures by Boosting, Jeffrey M. Walls and Ryan W. Wolcott