[mlpack] GSOC-2020 | Idea Proposal | Image Generation Modules
Hello Marcus/Ryan, I'm Rakesh Acharya , I wish to contribute to* mlpack library* by developing the *Image Generation* modules.Presently mlpack has *GAN,WGAN*.Many latest GAN models have disrupted the Image Generation field like BEGAN,Energy Based GAN,Manifold Matching GAN,Probabilistic GAN. *Yann LeCun described it as “the most interesting idea in the last 10 years in Machine Learning”. * Among the existing models *BEGAN/I-BEGAN* outruns most of the models,including Energy Based GANs.I hope it will be a good leap forward in building mlpack Image Generation modules. After my initial proposal* Marcus suggested me I-BEGAN* paper and after giving a thorough reading came to a conclusion that , though it has problem with disentagling factors results obtained are *very good with minimal Wassertian Distance based losses* and *maxmized mutual information.* *BEGAN : *https://arxiv.org/abs/1703.10717 *IBEGAN* : https://www.hindawi.com/journals/cin/2018/6465949/ I'd like to hear from you guys *suggestions regarding adding these modules to mlpack library* and growing the areas it can be used to *Image Generation.* Regards, Rakesh Acharya .D Computer Engineering,VIT Chennai Deep Learning,Computer Vision,Digital Signal Processing ___ mlpack mailing list mlpack@lists.mlpack.org http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack
[mlpack] GSOC proposal for Profiling for parallelism.
Hello Marcus/Ryan, I am Param Mirani and I want to contribute to MLpack by participating in GSOC 2020 in Profiling for Parallelism project. I have made some pull requests in trying to improve performance of the algorithms on multi-core processors using OpenMP. I had an idea and wanted to know your view on the same. I wanted to work on following algorithms in the 12 week program based on my knowledge of machine learning algorithms. 1)KNN 2)Decision Trees 3)Perceptron 4)Back-propagation I expect these algorithms to have an excellent speed-up when they use OpenMP. However I feel we would have a difficulty in deciding which parts of the algorithm based on various programs I write for benchmarking of these algorithms. There are some more algorithms which could use OpenMP but speed-up may not be that significant. Along with these I would also like to understand 2-3 more algorithms and work with them in a similar way. I'd like to know if the timeline I've proposed is realistic, if all assumptions are correct, and if there are any more algorithms that you would like me to work on while working on this project. Thanks, Param Mirani. ___ mlpack mailing list mlpack@lists.mlpack.org http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack
[mlpack] (no subject)
Hey Ryan/Marcus, Are there any current coordinates to start with, in "Profiling for Parallelization"? I want to know if any, to avoid any redundant work. Thanks -- Aman Pandey Webpage: https://johnsoncarl.github.io/aboutme/ LinkedIn: https://www.linkedin.com/in/amnpandey/ ___ mlpack mailing list mlpack@lists.mlpack.org http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack
