לוח שנה

א ב ג ד ה ו ש
 
 
 
 
 
1
 
2
 
3
 
4
 
5
 
6
 
7
 
8
 
9
 
10
 
11
 
12
 
13
 
14
 
15
 
16
 
17
 
18
 
19
 
20
 
21
 
22
 
23
 
24
 
25
 
26
 
27
 
28
 
29
 
30
 

Statistics Seminar: Yuval Benjamini

תאריך: 
ב', 27/11/2017 - 15:30 עד 16:30

מיקום: 
Hevra 4412

 

Title: Extrapolating expected accuracies for multi-class classification

 

Abstract: The difficulty of multi-class classification generally increases with the number of classes. 

This raises a natural question: Using data from a subset of the classes, can we predict how well a classifier will scale as the number of classes increases?

In this talk, I will present a framework that allows us to analyze this question. Assuming classes are sampled from a population (and some assumptions about the classifiers), we can identify how expected classification accuracy depends on the number of classes (k) via a specific cumulative distribution function. I will present a non-parametric method for estimating this function, which allows easy extrapolation to K>k. I will show empirical results for face-recognition and character-recognition tasks. Finally, I will discuss why the extrapolation problem may be important for neuroscientists, who are increasingly using mutliclass extrapolation accuracy as a proxy for richness of representation. 

This talk is based on joint work with Charles Zheng and Rakesh Achanta.

 

מרצה: 
Yuval Benjamini, Hebrew University