Scaling Up Machine Learning
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Published By Cambridge University Press

9781139042918
Latest Documents Most Cited Documents Contributed Authors Related Sources Related Keywords

Distributed Gibbs Sampling for Latent Variable Models

2012 ◽  
pp. 217-239
Author(s):  
Arthur Asuncion ◽  
Padhraic Smyth ◽  
Max Welling ◽  
David Newman ◽  
Ian Porteous ◽  
...  
Keyword(s):  
Gibbs Sampling ◽  
Latent Variable ◽  
Latent Variable Models

Massive SVM Parallelization Using Hardware Accelerators

2012 ◽  
pp. 127-147
Author(s):  
Igor Durdanovic ◽  
Eric Cosatto ◽  
Hans Peter Graf ◽  
Srihari Cadambi ◽  
Venkata Jakkula ◽  
...  
Keyword(s):  
Hardware Accelerators

scholarly journals Parallel Online Learning

2012 ◽  
pp. 283-306 ◽  
Author(s):  
Daniel Hsu ◽  
Nikos Karampatziakis ◽  
John Langford ◽  
Alex J. Smola
Keyword(s):  
Online Learning

Parallel Large-Scale Feature Selection

2012 ◽  
pp. 352-370 ◽  
Author(s):  
Jeremy Kubica ◽  
Sameer Singh ◽  
Daria Sorokina
Keyword(s):  
Feature Selection ◽  
Large Scale ◽  
Scale Feature

PSVM: Parallel Support Vector Machines with Incomplete Cholesky Factorization

2012 ◽  
pp. 109-126
Author(s):  
Edward Y. Chang ◽  
Hongjie Bai ◽  
Kaihua Zhu ◽  
Hao Wang ◽  
Jian Li ◽  
...  
Keyword(s):  
Support Vector Machines ◽  
Cholesky Factorization ◽  
Support Vector ◽  
Vector Machines ◽  
Incomplete Cholesky Factorization

Scaling Up Machine Learning: Introduction

2012 ◽  
pp. 1-20
Author(s):  
Ron Bekkerman ◽  
Mikhail Bilenko ◽  
John Langford
Keyword(s):  
Machine Learning ◽  
Scaling Up

scholarly journals Large-Scale Machine Learning Using DryadLINQ

2012 ◽  
pp. 49-68 ◽  
Author(s):  
Mihai Budiu ◽  
Dennis Fetterly ◽  
Michael Isard ◽  
Frank McSherry ◽  
Yuan Yu
Keyword(s):  
Machine Learning ◽  
Large Scale

Distributed Transfer Learning via Cooperative Matrix Factorization

2012 ◽  
pp. 331-351
Author(s):  
Evan Xiang ◽  
Nathan Liu ◽  
Qiang Yang
Keyword(s):  
Transfer Learning ◽  
Matrix Factorization
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