<div dir="ltr"><div>Dear all,</div><div><br></div><div>I am Marcos Pividori, a Computer Science student from the National University of Rosario, Argentina ([1]). I am currently finishing my degree. (5 year long degree)</div><div>I am writing because I am really interested in working this GSoC for mlpack.</div><div><br></div><div>After reading the different ideas, I got really interested in the project "Approximate Nearest Neighbor Search". I have read the discussions about this topic in the mlpack list, and I analysed the papers recommended for this project. </div><div>I know there is not much time left to the application deadline, I apologize for this. I thought it would be appropriate to read the main documentation, and get a general understanding of the project, before writing.</div><div><br></div><div>I have participated on some GSoC projects in the past: GSoC 2013 ([2][3]) for Haskell.org and GSoC 2015 ([4][5]) for OpenCog.</div><div>During 2014, I applied and was accepted to do an internship for iRobot, working during 4 months at the offices in Pasadena, US, on improving the software for the Roomba product.</div><div>As final project of the AI subject, I developed a computer Go player based on Monte Carlo Tree Search algorithm, in C++. In August 2015, I presented it to the EST 2015, Student Contest - 44 Argentine Conference of Informatics, where I got the first place. ([6] [7])</div><div><br></div><div>I would like to let you know that I am definitely really interested in this project. I am at the final steps of my degree, and I have to start working on my graduation thesis, but I haven't found a thesis topic yet. I see algorithms and data structures applied to ML as a potential topic. So, this GSoC project would give me the opportunity to go in depth in this area, working for a popular library, and gaining valuable experience from the community.</div><div><br></div><div>I have been reading the papers recommended for this topic. I think I have a general idea of the main methods for the Approximate Nearest Neighbor problem.</div><div>Also, I have installed the mlpack library and looked at the main code implementation.</div><div>So, I should split the project with these main goals:</div><div> + Implementation of approximate nearest neighbor search.</div><div> + Implementation of a command line tool (simple task).</div><div> + Comparisons between mlpack implementation and similar libraries, and writing of proper documentation.</div><div><br></div><div>About the implemenation of ann: do you have a preference on which method to use? Should we implement many of these different methods and compare their results?</div><div>I have found many different options in the literature:</div><div> + "An optimal algorithm for ANN Searching in Fixed dimensions" proposes to use BBD-Trees for the computation, and it is implemented in the ANN library. But I couldn't find more information on BBD trees. ANN library also uses KD-Trees.</div><div> + "An Investigation of Practical Approximate Nearest Neighbor Algorithms" proposes to use Spill-Trees (maybe Hybrid) with overlapping in points separation.</div><div> + "Fast approximate nearest neighbors with automatic configuration" reviews and compares the state of the art in ann. It mentioned the randomized kd-trees and k-means clustering trees as the most promising methods according to their results. FLANN library implements many of these methods.</div><div> + scikit-learn library implements Locality-Sensitive Hashing for ann.</div><div><br></div><div>I would be grateful if you could give me your opinion on this. Do you think I should focus on something in special?</div><div><br></div><div>I continue reading about this topic and preparing a proposal.</div><div><br></div><div>Thanks,</div><div><br></div><div>Marcos</div><div><br></div><div>[1] <a href="http://www.unr.edu.ar">http://www.unr.edu.ar</a></div><div>[2] <a href="http://gsoc2013cwithmobiledevices.blogspot.com.ar">http://gsoc2013cwithmobiledevices.blogspot.com.ar</a></div><div>[3] <a href="http://github.com/MarcosPividori/GSoC-Communicating-with-mobile-devices">http://github.com/MarcosPividori/GSoC-Communicating-with-mobile-devices</a></div><div>[4] <a href="http://wiki.opencog.org/wikihome/index.php/Haskell_Bindings_-_GSoC_2015">http://wiki.opencog.org/wikihome/index.php/Haskell_Bindings_-_GSoC_2015</a></div><div>[5] <a href="http://github.com/MarcosPividori/atomspace/tree/master/opencog/haskell">http://github.com/MarcosPividori/atomspace/tree/master/opencog/haskell</a></div><div>[6] <a href="http://44jaiio.sadio.org.ar/sites/default/files/est215-224.pdf">http://44jaiio.sadio.org.ar/sites/default/files/est215-224.pdf</a></div><div>[7] <a href="http://github.com/MarcosPividori/Go-player">http://github.com/MarcosPividori/Go-player</a></div></div>