![Map-Reduce???
• It’s just a framework
• You can also implement it by reading the
paper[1]. :)
• Hadoop is one implementation. (Apache +
Yahoo)
• Google’s implementation is not made
public.](https://image.slidesharecdn.com/projectprogress-090702024937-phpapp01/85/Project-Progress-6-320.jpg)
Project Progress
- 2. What we’ve been doing(1) • Hacking Hadoop API. • Writing different kinds of programs to understand it. (Not CV programs) • Adaboost • SIFT, SURF • Reading, Reading
- 3. Segmentation ROI ROI
- 4. segmentation with overlap get SIFT/SURF descriptor for partial segments reduce no. of descriptors by grouping them. region of interest (positive&negative) count the frequency of occurrence of visual words AdaBoost
- 5. Methodology • For simplicity, assume the the same image is stored on all slave nodes. • Use ROI to run the algorithm. • Hopefully this will make it easier for the “Reduce”
- 6. Map-Reduce??? • It’s just a framework • You can also implement it by reading the paper[1]. :) • Hadoop is one implementation. (Apache + Yahoo) • Google’s implementation is not made public.
- 7. Map-Reduce for Machine Learning on Multi-core
- 8. Introduction • Algorithm fitting Statistical Query Model may be written in a certain “summation form” • Divide into data set into as many pieces as the number of cores.
- 9. • Algorithm fitting Statistical Query Model may be written in a certain “summation form” • Divide into data set into as many pieces as the number of cores.
- 10. Algorithms(1) • Locally Weight Linear Regression • Naive Bayes • Gaussian Discriminative Analysis • k-means • Logistic Regression • Neural Network
- 11. Algorithms(2) • Principal Components Analysis • Independent Components Analysis • Expansion Maximization • Support Vector Machine
- 12. Example (LWLR) divide the computation among different mappers to compute: 2 reducers sum up the partial values for A and b and finally computes the solution
- 13. Experiment Result • Used UCI Machine Learning repository • Used only 2 cores. • 1.9x times faster • 54 times speed up on 64 cores. • Speed up is achieved by “throwing cores” only