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Xi He
http://xihey.com/intro
He who hesitates is lost. He who hesitates is lost. I am a second year Ph.D. student in Industrial and Systems Engineering. Working with Prof. Martin Takáč. On developing practical algorithms and their theoretical analysis for large scaled optimization problems in machine learning . Before coming to Lehigh, I earned my undergraduate degree in School of Mathematical Sciences. Tianjin China. After that, I continued my master degree under supervisor of Prof. Qingzhi Yang. At Princeton, NJ.
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Xi He
http://xihey.com/works
He who hesitates is lost. He who hesitates is lost. Large-scale optimization algorithms and its applications in machine learning. More specifically,. Stochastic Gradient Methods (SGD, SDCA, SVRG, etc.) fors Large-scale Nonlinear Optimization. Optimization Method in Deep Neural Network. Large Scale Distributed Hessian-Free Optimization for Deep Neural Network, with Mudigere Dheevatsa, Martin Takáč. Asynchronous Distributed Stochastic dual (Block) Coordinate Ascent Method, with Martin Takáč. Designed compe...
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Tag: Editor | Xi He
http://xihey.com/tags/Editor
He who hesitates is lost. He who hesitates is lost.
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Category: Maths | Xi He
http://xihey.com/categories/Maths
He who hesitates is lost. He who hesitates is lost. Can CG verify that a matrix is positive definite? Notes on Introductory Lectures on Convex Optimization ( I ).
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Xi He
http://xihey.com/more
He who hesitates is lost. He who hesitates is lost. Address(office): 358 H.S. Mohler Laboratory, 200 West Packer Avenue, Bethlehem, PA 18015. Address(home): 837 Cedar Hill Drive, Allentown, PA, 18109. Email: heeryerate@gmail.com, xih314@lehigh.edu.
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Handy commands, Troubleshooting and Collection | Xi He
http://xihey.com/2016/04/25/handy_commands
He who hesitates is lost. He who hesitates is lost. Handy commands, Troubleshooting and Collection. Command is very helpful if you want to have multiple shells running in one terminal window. Also, it can help you run a program persistently (even if a terminal window breaks or closes). Create a session. You can easily exit current session by. Or terminate a session by. List all sessions you have. Command is used to store and view (both at the same time) the output of any other command. Git rm -r - cached .
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Engineering Research at Lehigh University, P.C. Rossin College of Engineering and Applied Science
http://www.lehigh.edu/engineering/research/index.html
Skip to Main Content. Creating new knowledge through groundbreaking research while sharing meaningful insights with tomorrow’s innovators: Lehigh is unique among competitive research universities in insisting upon a true balance between the two. Lehigh clusters scholarly and research capabilities to provide fertile ground for intellectually-stimulating research and practical insight into the realities of their chosen fields. Energy and the Environment. The ability to locate, observe, manipulate and fabri...
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Tag: Hexo | Xi He
http://xihey.com/tags/Hexo
He who hesitates is lost. He who hesitates is lost. Reminders on maintaining this Blog. Use GitHub and Hexo to build a Blog.
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Reminders on maintaining this Blog | Xi He
http://xihey.com/2015/08/20/reminder_on_maintaining_website
He who hesitates is lost. He who hesitates is lost. Reminders on maintaining this Blog. Create a new post. Hexo new [layout] titlename (ex. hexo new "My New Post". Generate static files and test locally. Generate static files and deploy to remote sites. Host an image by Google Drive or ImageShack. Upload your image to your. Change link sharing to. Public on the web. Copy the sharing link and transfer it by gdURL. Add webcounter by Webcounter. Handy commands, Troubleshooting and Collection.
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Notes on Introductory Lectures on Convex Optimization ( I ) | Xi He
http://xihey.com/2016/05/23/Notes-on-Introductory-Lectures-on-Convex-Optimization-I
He who hesitates is lost. He who hesitates is lost. Notes on Introductory Lectures on Convex Optimization ( I ). This note is based on a book Introductory Lectures on Convex Optimization. Chapter 1: Nonlinear Optimization. Can CG verify that a matrix is positive definite?
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