CS 229 Machine Learning
Final Projects, Autumn 2006

Using Atomic Actions to Control Snake Robot Locomotion. Joseph Koo. [pdf]

Minimizing System Correlation in SVM Training. Luciana Ferrer. [pdf]

Dimensionality Reduction using Noisy Distance Data. Pratik Biswas. [pdf]

Temporal Ordering of Event Descriptions. Nate Chambers and Shan Wang. [pdf]

Training Log Linear Models Using Smoothed Hamming Loss. Olga Russakovsky. [pdf]

Just Keep Flying: Machine Learning for UAV Gust Soaring. Geoff Bower and Alex Naiman. [pdf]

Learning Planar Geometric Scene Context Using Stereo Vision. Paul Baumstarck and Bryan Brudevold and Paul Reynolds. [pdf]

KNN for Netflix. Ted Hong and Dimitris Tsamis. [pdf]

Object Identification in Images. Mark Mao. [pdf]

Intelligent Rankings. Hau Jia Chew and Dimitris Economou and Raylene Yung. [pdf]

"Combination of Experts" Approach to Image Boundary Detection. David Cohen and Jim Rodgers. [pdf]

Auto-Tagging the Facebook. Jorge Ortiz and Jonathan Michelson. [pdf]

Segmenting Descending Aorta Using Machine Learning. Rahul Choudhury. [pdf]

Structure-Informed RNA Sequence Alignment using Discriminative Models. Gregory Goldgof. [pdf]

Musical Instrument Detection. Gautham J. Mysore and Gregory Sell and SongHui Chon. [pdf]

Breaking it Down: The World as Legos. Benjamin Savage and Eric Chu. [pdf]

Learning 3-D Scene Structure from a Single Still Image. Min Sun and Rajiv Agarwal.

Language Classification in Multilingual Documents. Gorkem Ozbek, Itamar Rosenn and Eric Yeh. [pdf]

Rotation-Invariant Sparse Coding. Mark Linsey, Nathan Pflueger, Ryan Timmons. [pdf]

Knowledge Based Reconstruction of the Transcriptional Regulatory Network in Yeast. Seok Chang Ryu and Junhee Seok. [pdf]

4-D Interest Maps for Direct Fovea Attention-Based Systems. Mick Garvey, Itai Katz, and Megan Wachs. [pdf]

System Identification of DragonFly UAV via Bayesian Estimation. Sun Hwan Lee and Youn Mi Park. [pdf]

Dimensionality-Reduction of Neural Data. Zuley Rivera Alvidrez and Rachel Kalmar. [pdf]

Image processing of wildtype and mutant bacterial cells. Sun-Hae Hong and Meng How Tan. [pdf]

Dimension Reduction of Image Manifolds. Arian Maleki. [pdf]

Learning Techniques to aid Pose Estimation via SIFT. Sean Augenstein. [pdf]

Classifying fMRI Data. Christopher Archibald and Evan Millar. [pdf]

Investigating Copy Number Variation in Cancer. Imran Haque and Sharareh Noorbaloochi.

Computational Beauty Analysis. Elizabeth Day and Fawntia Fowler. [pdf]

Programming-By-Example Gesture Recognition. Kevin Gabayan and Steven Lansel. [pdf]

Teaching STAIR to Identify and Manipulate Tools. Debbie Meduna. [pdf]

Netflix Prize Project. Jack Cheng, Virginia Chu, Yang Wang. [pdf]

Pose Estimation From Occluded Images. Kanako Hayashi, Lionel Heng and Vikram Srivastava. [pdf]

Predicting how Netflix users will rate movies using logistic regression and probabilistic modelling. Adam Sadovsky and Xing Chen. [pdf]

Hierarchical Sparse Coding. Ian Post. [pdf]

Mining Feelings. Luis Adarve-Martin, Jie Li and Eelan Chia. [pdf]

Market Making With Machine Learning. Maoching Foo and Wei Zhao and Yu Chen. [pdf]

Beat Induction. Peerapong Dhangwatnotai, Rajendra Shinde and Pawin Vongmasa. [pdf]

Predicting Visual Saliency and Saccade Probability. Bob Schafer, Boyko Kakaradov, Mindy Chang. [pdf]

Extracting Meeting Topics Using Speech And Documents. Katherine Brainard, Tim Chang, and Kari Lee. [pdf]

Detecting Corporate Fraud: An Application of Machine Learning. Ophir Gottlieb and Curt Salisbury and Howard Shek and Vishal Vaidyanathan. [pdf]

Matrix Factorization for Collaborative Prediction. Alex Kleeman, Sylvie Denuit, Nick Hendersen. [pdf]

Face Orientation Estimation in Smart Camera Networks. Chung-Ching Chang. [pdf]

Super-resolution. Andrew Wong and Yusuf Ozuysal. [pdf]

Optical Illusion. Sara Bolouki. [pdf]

Object Recognition from 3D Point Clouds. Antoine El Daher and Sehyuk Park. [pdf]

Use of KNN and K-Means for the Netflix Prize. Ted Hong, Brian Sa, Patrick Shih, Dimitris Tsamis. [pdf]

Factor-analysis with partially observed training data. Paul Csonka and Barrett Heyneman and Salomon Trujillo. [pdf]

A Machine Learning Approach to Opponent Modeling in General Game Playing. Tyler Griffin Hicks-Wright and Eric Daniel Schkufza. [pdf]

Sparse Coding Invariance. Daniel Wagner, David Ho, and Chaitu Ekanadham. [pdf]

Automatically clustering WordNet senses. Christopher Thad Hughes and Sushant Prakash. [pdf]

SQUINT: Identifying Relevant Sections of a Web page for a Web Search Query. Siddharth Jonathan and Jyotika Prasad and Riku Inoue. [pdf]

Detecting Digital Forgeries Using SVMs and Lighting Inconsistencies. David Ziegler. [pdf]

Waveform-based Musical Genre Classification. Charles Tripp, Hochak Hung and Manos Pontikakis. [pdf]

Machine Learning Based Botnet Detection. Vaibhav Nivargi, Mayukh Bhaowal, Teddy Lee. [pdf]

Machine Learning applied to Building Performance Metrics. Tobias Maile. [pdf]

Automatic Identification of Red-Eye in Photos. Paul Cuff. [pdf]

Machine Learning with a Lego Mindstorms Robot. Julie Townsend. [pdf]

Applying sparse coding to speech. Stephan Hyeonjun Stiller and Helen Hui Lam Kwong.

Determining the Information Value Of Tags. Paul Heymann. [pdf]

Computational Identification and Prediction of Tissue-Specific Alternative Splicing. Eric Van Nostrand. [pdf]

Predicting connection quality in peer-to-peer real-time video streaming systems. Alex Giladi and Jeonghun Noh. [pdf]

Predicting 3D Arm Trajectories. Cynthia Chestek. [pdf]

Are You Hot Or Not?. Jim Hefner and Roddy Lindsay. [pdf]

Explaining Preference Learning. Alyssa Glass. [pdf]

Rotten Tomatoes: Sentiment Classification in Movie Reviews. Alyssa Liang. [pdf]

NFL Project (Predicting the outcome of NFL games). Babak Hamadani. [pdf]

Learning to Test. Michael Munie. [pdf]

Predicting Movie Preferences. Ian Baker. [pdf]

Learning Bayesian Networks in Presence of Missing Data. Narges Bani Asadi. [pdf]

Understanding Civil War and Economic Growth. Francine Anene.

Stock Trading with Recurrent Reinforcement Learning (RRL). Gabriel Molina. [pdf]