A Framework for Machine Learning and Data Mining in the Cloud [12]

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1- INTRODUCTION

2- MLDM ALGORITHM PROPERTIES

2.1 Graph Structured Computation

2.2 Asynchronous Iterative Computation

2.3 Dynamic Computation

2.4 Serializability

Figure 1

3 DIST. GRAPHLAB ABSTRACTION

3.1 GraphLab Execution Model

3.2 Consistency Models

4 DISTRIBUTED GRAPHLAB DESIGN

Figure 2: System Overview

4.1 Distributed Data Graph

4.2 Distributed GraphLab Engines

4.3 Fault Tolerance

4.4 System Design

5- APPLICATIONS

6- STRENGTHS AND LIMITATIONS

7- CURRENT STATE-OF-THE-ART

8- RELATED WORK

9- CONCLUSION

REFERENCES

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