Lecture 5 Flashcards
1
Q
What is the runtime of the OLS estimation with one predictor?
A
![](https://s3.amazonaws.com/brainscape-prod/system/cm/396/495/167/a_image_thumb.png?1663596560)
2
Q
How do we derive the runtime of the multiple OLS estimator?
A
![](https://s3.amazonaws.com/brainscape-prod/system/cm/396/495/422/a_image_thumb.png?1663597030)
3
Q
What is the pseudocode and runtime for matrix multiplication?
A
![](https://s3.amazonaws.com/brainscape-prod/system/cm/396/495/934/a_image_thumb.png?1663596950)
4
Q
How can we “divide and conquer” matrix multiplication?
A
![](https://s3.amazonaws.com/brainscape-prod/system/cm/396/496/220/a_image_thumb.png?1663598381)
5
Q
What is Strassens matrix multiplication algorithm?
A
![](https://s3.amazonaws.com/brainscape-prod/system/cm/396/499/703/a_image_thumb.png?1663598417)
6
Q
What is a classification problem?
A
![](https://s3.amazonaws.com/brainscape-prod/system/cm/396/499/825/a_image_thumb.png?1663598466)
7
Q
What is k-nearest neighbours? What are the steps for the 1D version of this problem?
A
![](https://s3.amazonaws.com/brainscape-prod/system/cm/396/500/022/a_image_thumb.png?1663598554)
8
Q
How to implement a fast k-nearest neighbour algorithm?
A
![](https://s3.amazonaws.com/brainscape-prod/system/cm/396/500/314/a_image_thumb.png?1663598592)