PPT-Factorbird : a Parameter Server Approach to Distributed Matrix Factorization

Author : celsa-spraggs | Published Date : 2018-02-24

Sebastian Schelter Venu Satuluri Reza Zadeh Distributed Machine Learning and Matrix Computations workshop in conjunction with NIPS 2014 Latent Factor Models

Presentation Embed Code

Download Presentation

Download Presentation The PPT/PDF document "Factorbird : a Parameter Server Approach..." is the property of its rightful owner. Permission is granted to download and print the materials on this website for personal, non-commercial use only, and to display it on your personal computer provided you do not modify the materials and that you retain all copyright notices contained in the materials. By downloading content from our website, you accept the terms of this agreement.

Factorbird : a Parameter Server Approach to Distributed Matrix Factorization: Transcript

Sebastian Schelter Venu Satuluri Reza Zadeh Distributed Machine Learning and Matrix Computations workshop in conjunction with NIPS 2014 Latent Factor Models Given M sparse n x . Andersen Jun Woo Park Alexander J Smola Amr Ahmed Vanja Josifovski James Long Eugene J Shekita BorYiing Su Carnegie Mellon University Baidu Google muli dga junwoop cscmuedu alexsmolaorg amra vanjaj jamlong shekita boryiingsu googlecom Abstract Data Analysis on . MapReduce. Chao Liu, Hung-. chih. Yang, Jinliang Fan, Li-Wei He, Yi-Min Wang. Internet Services Research Center (ISRC). Microsoft Research Redmond. Internet Services Research Center (ISRC). . Networks. Distributed. . P. arameter. . Networks. Distributed. . Parameter. . Networks. 1.. The . electric. and . magnetic. . power. . distribute. . homogeneously. . along. . the. . wire. Recovering latent factors in a matrix. m. movies. v11. …. …. …. vij. …. vnm. V[. i,j. ] = user i’s rating of movie j. n . users. Recovering latent factors in a matrix. m. movies. n . users. T(A) . 1. 2. 3. 4. 6. 7. 8. 9. 5. 5. 9. 6. 7. 8. 1. 2. 3. 4. 1. 5. 2. 3. 4. 9. 6. 7. 8. A . 9. 1. 2. 3. 4. 6. 7. 8. 5. G(A) . Symmetric-pattern multifrontal factorization. T(A) . 1. 2. 3. 4. 6. 7. 8. under Additional Constraints. Kaushik . Mitra. . University . of Maryland, College Park, MD . 20742. Sameer . Sheorey. y. Toyota Technological Institute, . Chicago. Rama . Chellappa. University of Maryland, College Park, MD 20742. and. Collaborative Filtering. 1. Matt Gormley. Lecture . 26. November 30, 2016. School of Computer Science. Readings:. Koren. et al. (2009). Gemulla. et al. (2011). 10-601B Introduction to Machine Learning. By M. Li, D. Anderson, J. Park, A. . Smola. , A. Ahmed, V. . Josifovski. , J. Long E. . Shekita. , B. Su. . EECS 582 – W16. 1. Outline. Motivation. Parameter Server architecture. Why is it special?. Grayson Ishihara. Math 480. April 15, 2013. Topics at Hand. What is Partial Pivoting?. What is the PA=LU Factorization?. What kinds of things can we use these tools for?. Partial Pivoting. Used to solve matrix equations. m. movies. v11. …. …. …. vij. …. vnm. V[. i,j. ] = user i’s rating of movie j. n . users. Recovering latent factors in a matrix. m. movies. n . users. m. movies. x1. y1. x2. y2. ... ... …. Dileep Mardham. Introduction. Sparse Direct Solvers is a fundamental tool in scientific computing. Sparse factorization can be a challenge to accelerate using GPUs. GPUs(Graphics Processing Units) can be quite good for accelerating sparse direct solvers. Gemar. 11-10-12. Advisor: Dr. . Rebaza. Overview. Definitions. Theorems. Proofs. Examples. Physical Applications. Definition 1. We say that a subspace S or . R. n. is invariant under . A. nxn. , or A-invariant if:. Madan Musuvathi. . Visiting Professor, UCLA . Principal Researcher, Microsoft Research. Course Project. Write-ups due June 1. st. Project presentations . 12 presentations, 10 mins each, 15 min slack. Sebastian . Schelter. , . Venu. . Satuluri. , Reza . Zadeh. Distributed Machine Learning and Matrix Computations workshop in conjunction with NIPS 2014. Latent Factor Models. Given . M. sparse. n . x .

Download Document

Here is the link to download the presentation.
"Factorbird : a Parameter Server Approach to Distributed Matrix Factorization"The content belongs to its owner. You may download and print it for personal use, without modification, and keep all copyright notices. By downloading, you agree to these terms.