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City Scottsdale / / Country United States / / Currency USD / / / IndustryTerm different applications / by-product / sense to consider algorithms / dot products / implicit regularization properties underlying approximation algorithms / ow-based approximation algorithm / eigenvalue algorithms / different approximation algorithms / large-scale applications / algorithmic tool / medium-scale applications / iterative algorithm / approximation algorithm / black box algorithm / possible algorithm / given hardware / trivial brute force algorithm / ow-based approximation algorithms / meaningful solutions / breadth-first search / Web-scale graphs / spectral algorithms / divide-and-conquer algorithms / iterative algorithms / Web-scale data matrices / given and modeled algorithms / spectral-based approximation algorithm / approximation algorithms / numerical applications / Web-scale computations / spectral algorithm / mediumscale applications / remote sensing applications / Internet applications / massive data applications / downstream applications / unstable algorithm / neural network / graph approximation algorithms / push algorithm / data analysis applications / depth-first search / given algorithm / worst-case algorithms / parallel computing applications / diffusion-based approximation algorithms / approximate solution / iterative gradient descent algorithm / banking / consumer applications / locally-biased spectral-based algorithms / airline reservation systems / Web graph / computing / backward stable algorithm / numerical algorithm / search engine / scientific computing / recent algorithms / larger-scale applications / / Organization Very Large-scale Data Analysis Michael W. Mahoney Department / Stanford University Stanford / / Person Metis / Michael W. Mahoney / / / Position statistician / domain scientist / computer scientist / downstream analyst / General / analyst / / ProgrammingLanguage SQL / / ProvinceOrState Arizona / / Technology Lanczos algorithms / RAM / good algorithm / spectral algorithm / graph approximation algorithms / trivial brute force algorithm / Av / remote sensing / relational database / ow-based algorithms / search engine / machine learning / flow-based methods.20 Spectral algorithms / random access / viral marketing / worst-case algorithms / so-called push algorithm / given and modeled algorithms / implicit regularization properties underlying approximation algorithms / iterative gradient descent algorithm / ow-based approximation algorithms / black box algorithm / possible algorithm / given well-conditioned problem / 7 certain algorithms / two different approximation algorithms / above three diffusion-based approximation algorithms / flow-based algorithm / neural network / load balancing / locally-biased spectral-based algorithms / ow-based approximation algorithm / S⊆V Flow-based algorithms / approximation algorithm / eigenvalue algorithms / DNA Chip / given algorithm / three approximation algorithms / numerical algorithm / training algorithm / approximation algorithms / different approximation algorithms / iterative algorithm / backward stable algorithm / push algorithm / divide-and-conquer algorithms / spectral-based approximation algorithm / /
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Approximate Computation and Implicit Regularization for Very Large-scale Data Analysis Michael W. Mahoney Department of Mathematics Stanford University Stanford, CA 94305