Hi Mudit, <br><br>Good to know about you.<br><div class="gmail_quote"><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><span style="font-family:arial,sans-serif;font-size:13px;border-collapse:collapse;color:rgb(34,34,34)"><div>
<br></div><div>I successfully completed my <b>Google Summer of Code - 2011</b> for the <b>Center for the study of Complex systems - University of Michigan</b>. I implemented various <b>algorithms (ant colony, random walk etc.)</b> related to computational intelligence in Repast S (<b>Coded in Groovy, Java</b>) and wrote <b>extensive documentations and tutorial</b> for the related models with <b>literature reviews</b> on the topics. My <b>contributions to Repast S was a part of the latest release of the software</b>. The detailed documentation and code can be found here:<a href="http://code.google.com/p/cscs-repast-demos/wiki/Mudit" style="color:rgb(17,85,204)" target="_blank">http://code.google.com/p/cscs-repast-demos/wiki/Mudit</a> I have also worked on various projects related to implementation of Machine Learning and Bio-Inspired Evolutionary Algorithms.You can check the code and some documentation on the same on <a href="http://code.google.com" target="_blank">code.google.com</a> my user profile is : <a href="http://code.google.com/u/110675325175605367090/" target="_blank">http://code.google.com/u/110675325175605367090/</a></div>
</span></blockquote><div><br>Seems your previous experience with machine learning will help you.<br> <br></div><blockquote class="gmail_quote" style="margin:0pt 0pt 0pt 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex">
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<div><br></div><div>I am interested in applying for the project - <b>"Learning to Rank</b><span>". I have read the pointers on the ideas page and some literature about it. I was thinking, based on my literature review, that something on the lines on Multi-layer Perceptron network with Ant Colony Optimization or an Improved random Forest could be a good option. I selected the same because of my experience on the topic. Although any further details/pointers to the projects would be greatly appreciated. I would also like to request you to please let me know about any specific detail related to the project that is required in the proposal (apart from the ones mentioned on the page)</span></div>
</span></blockquote><div><br>There have been plenty of algorithms proposed in the recent past. Based on your choice of ML technique, you can choose one. As you are interested in Neural Net based approaches, ListNet [1], RankNet [2], ListMLE [3], LamdaRank [4] can be of your interest and if you want to explore the random forests based approaches then [5] can be checked out.<br>
<br>[1] Learning to rank: from pairwise approach to listwise approach<br>[2]<font> Learning to Rank using Gradient Descent<br>[3] Listwise Approach to Learning to Rank - Theory and Algorithm<br>[4] Learning to Rank with Nonsmooth Cost Functions<br>
[5] Learning to rank with extremely randomized trees<br><br><br>Regards,<br>Parth.<br><br></font>
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<div><span></span> </div><div><span>Thank you for your time. Hope to hear from you soon.</span></div><div><span></span> </div><div><span>Best Regards, </span></div><div><span></span> </div><div><span>Mudit Raj Gupta </span></div>
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