Title
Compressing and Teaching for Low VC-Dimension
Abstract
In this work we study the quantitative relation between VC-dimension and two other basic parameters related to learning and teaching. Namely, the quality of sample compression schemes and of teaching sets for classes of low VC-dimension. Let C be a binary concept class of size m and VC-dimension d. Prior to this work, the best known upper bounds for both parameters were log(m), while the best lower bounds are linear in d. We present significantly better upper bounds on both as follows. We construct sample compression schemes of size exp(d) for C. This resolves a question of Littlest one and Warmuth (1986). Roughly speaking, we show that given an arbitrary set of labeled examples from an unknown concept in C, one can retain only a subset of exp(d) of them, in a way that allows to recover the labels of all other examples in the set, using additional exp(d) information bits. We further show that there always exists a concept c in C with a teaching set (i.e. A list of c-labeled examples uniquely identifying c in C) of size exp(d) log log(m). This problem was studied by Kuhlmann (1999). Our construction also implies that the recursive teaching (RT) dimension of C is at most exp(d) log log(m) as well. The RT-dimension was suggested by Zilles et al. And Doliwa et al. (2010). The same notion (under the name partial-ID width) was independently studied by Wigderson and Yehuday off (2013). An upper bound on this parameter that depends only on d is known just for the very simple case d=1, and is open even for d=2. We also make small progress towards this seemingly modest goal.
Year
DOI
Venue
2015
10.1109/FOCS.2015.12
IEEE Symposium on Foundations of Computer Science
Keywords
Field
DocType
PAC learning,VC dimension,sample compression schemes,recursive teaching dimension
Log-log plot,Discrete mathematics,VC dimension,Combinatorics,Teaching dimension,Concept class,Upper and lower bounds,Mathematics,Recursion,Binary number
Conference
ISSN
Citations 
PageRank 
0272-5428
8
0.51
References 
Authors
47
4
Name
Order
Citations
PageRank
Shay Moran16327.30
Amir Shpilka2109564.27
Avi Wigderson382051064.31
Amir Yehudayoff453043.83