Large Scale Machine Learning

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Date: 2010-09-25 15:14:57 Multivariate statistics Singular value decomposition Linear algebra Matrix theory Information retrieval Latent semantic indexing Spectral clustering Principal component analysis Kernel principal component analysis Statistics Algebra Mathematics		Large Scale Machine Learning Add to Reading List Source URL: www.sanjivk.com Download Document from Source Website File Size: 476,51 KB Share Document on Facebook

	Week 6 (due May 14) Reading: Srednicky, sectionIn this exercise you will apply the Faddeev-Popov procedure to simplify some finite-dimensional integrals over spaces of matrices. Such integrals are known as matrix DocID: 1v5Qz - View Document
	Geometry of Neural Network Loss Surfaces via Random Matrix Theory Jeffrey Pennington 1 Yasaman Bahri 1 Abstract Understanding the geometry of neural network DocID: 1v21M - View Document
	Understanding and Improving Deep Learning with Random Matrix Theory Jeffrey Pennington Google Brain, NYC November 8, 2017 DocID: 1uOTm - View Document
	Week 6 (due Feb. 19) Reading: Srednicki, sectionsNB: In the following problems it is better to use FeynCalc package for Mathematica than to do gamma-matrix traces by hand. See http://www.feyncalc.org/ for detaile DocID: 1uHIP - View Document
	Compressed Sensing Theory Projection Matrix Theory DocID: 1uwVY - View Document