Differences
This shows you the differences between two versions of the page.
| Both sides previous revision Previous revision Next revision | Previous revision Next revision Both sides next revision | ||
|
courses:rg:2012:distributed-perceptron [2012/12/16 17:08] machacek |
courses:rg:2012:distributed-perceptron [2012/12/16 21:32] machacek |
||
|---|---|---|---|
| Line 1: | Line 1: | ||
| ====== Distributed Training Strategies for the Structured Perceptron - RG report ====== | ====== Distributed Training Strategies for the Structured Perceptron - RG report ====== | ||
| + | |||
| + | ===== Presentation ===== | ||
| + | |||
| + | ==== 3 Structured Perceptron ==== | ||
| + | |||
| + | ==== 4 Distributed Structured Perceptron ==== | ||
| + | |||
| + | * Motivation: There is no straightforward way to make the standard perceptron algorithm parallel. | ||
| + | |||
| + | === 4.1 Parameter Mixing === | ||
| + | |||
| + | === 4.2 Iterative Parameter Mixing === | ||
| + | |||
| + | ==== 5 Experiments ==== | ||
| + | |||
| + | |||
| ===== Questions ===== | ===== Questions ===== | ||
| Line 38: | Line 54: | ||
| w = [0, 0.6] | w = [0, 0.6] | ||
| + | |||
| + | | ||
| ==== Question 2 ==== | ==== Question 2 ==== | ||
| Line 79: | Line 97: | ||
| N = argmax_N f(N, T, F, ...) | N = argmax_N f(N, T, F, ...) | ||
| f = ? | f = ? | ||
| + | |||
| + | **Answer:** | ||
| + | |||
| + | We have not concluded on a particular formula. | ||
| + | * It also depends on convergence criteria. | ||
| + | * With no time limitation, the serial algorithm would have the least energy consumption. | ||
| + | * With time limitation, we should use as least shards to meet the time limitation. | ||