rcurtin_irc changed the topic of #mlpack to: mlpack: a scalable machine learning library (https://www.mlpack.org/) -- channel logs: https://libera.irclog.whitequark.org/mlpack -- NOTE: messages sent here might not be seen by bridged users on matrix, gitter, or slack
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<vaibhavp[m]> zoq: rcurtin: I will update my proposal to accommodate these changes if you have no objection.
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<_slack_mlpack_28> 1 year working on large model training acceleration and deploying memory optimization method DTR into PyTorch, which has given me sufficient experience in DL framework development, especially in PyTorch. Although I’m totally new to open source contribution and the mlpack community, I’m really enthusiastic to contribute to this project and I wish my experience could help me with it. Check out with my LinkedIn profile if any of you
<_slack_mlpack_28> Hello everyone! I am Yang ZHAO, a 2nd year’s master student at the University of Tokyo, majoring in Computer Science. My research and career interest is machine learning system, especially large model training acceleration, video memory optimization, etc. Therefore, I’m very keen on the project Improvisation and Implementation of ANN Modules in mlpack involved in GSoC'23. I have been in an internship in SenseTime Co. for more than
<_slack_mlpack_28> are interested in my experience: <https://www.linkedin.com/in/yang-zhao-0226/>
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<zoq[m]> <vaibhavp[m]> "I also think, the Layer class..." <- If you can explain this in your proposal, why you think vector is a good idea, perfect.
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<SuvarshaChennare> zoq rcurtin [GSoC 2023: Enhance CMA-ES] (https://docs.google.com/document/d/1TqqVAIbK_vCnfYODhADP2_TDC8HAkrjm7g1rbuap-Kc/edit?usp=sharing). I would greatly appreciate any feedback on the content of the proposal. Thank you for taking the time to do so!
<SuvarshaChennare> s///
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<vaibhavp[m]> <zoq[m]> "If you can explain this in..." <- zoq: For an example, I have created [split layer](https://github.com/mrdaybird/mlpack-dag-network/blob/main/split.cpp). This layer takes in a single matrix as an input and splits multiple sub-matrices as output. The output is a reference of vector composed of matrices created with 'MakeAlias' from the original layer outputs. So, the outputs are sent to appropriate layers, without making
<vaibhavp[m]> additional copies.
<vaibhavp[m]> * and splits into multiple sub-matrices
<vaibhavp[m]> * zoq: For example, I have created [split layer](https://github.com/mrdaybird/mlpack-dag-network/blob/main/split.cpp). This layer takes in a single matrix as an input and splits into multiple sub-matrices as output. The output is a reference of vector composed of matrices created with 'MakeAlias' from the original layer outputs. So, the outputs are sent to appropriate layers, without making additional copies.
ShivaniSorte[m] has joined #mlpack
<vaibhavp[m]> Hey everyone! I have updated my proposal, to make additional changes and added some algorithms. Here's the link:[Directed Graph-based Neural Networks in mlpack](https://docs.google.com/document/d/1vxHrSc1glWvUqfxIodAql03rzYV9F_9ls4bT3Pwso6A/edit?usp=sharing). If you have any feedback please share. Thank you!
<vaibhavp[m]> * Hey everyone! I have updated my proposal, to make additional changes and added some additional details. Here's the link to the proposal:[Directed Graph-based Neural Networks in mlpack](https://docs.google.com/document/d/1vxHrSc1glWvUqfxIodAql03rzYV9F_9ls4bT3Pwso6A/edit?usp=sharing). If you have any feedback please share. Thank you!
<vaibhavp[m]> * Hey everyone! I have updated my proposal, to make additional changes and added some additional details. Here's the link to the proposal: [Directed Graph-based Neural Networks in mlpack](https://docs.google.com/document/d/1vxHrSc1glWvUqfxIodAql03rzYV9F_9ls4bT3Pwso6A/edit?usp=sharing). If you have any feedback please share. Thank you!
<vaibhavp[m]> * Hey everyone! I have updated my proposal to include some additional details. Here's the link to the proposal: [Directed Graph-based Neural Networks in mlpack](https://docs.google.com/document/d/1vxHrSc1glWvUqfxIodAql03rzYV9F_9ls4bT3Pwso6A/edit?usp=sharing). If you have any feedback please share. Thank you!