VC-dimensions of nondeterministic finite automata for words of equal
length
- URL: http://arxiv.org/abs/2001.02309v2
- Date: Wed, 4 Aug 2021 18:28:10 GMT
- Title: VC-dimensions of nondeterministic finite automata for words of equal
length
- Authors: Bj{\o}rn Kjos-Hanssen, Clyde James Felix, Sun Young Kim, Ethan Lamb,
Davin Takahashi
- Abstract summary: Let $NFA_b(q)$ denote the set of languages accepted by nondeterministic finite automata with $q$ states over an alphabet with $b$ letters.
Let $B_n$ denote the set of words of length $n$.
- Score: 2.099922236065961
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Let $NFA_b(q)$ denote the set of languages accepted by nondeterministic
finite automata with $q$ states over an alphabet with $b$ letters. Let $B_n$
denote the set of words of length $n$. We give a quadratic lower bound on the
VC dimension of \[
NFA_2(q)\cap B_n = \{L\cap B_n \mid L \in NFA_2(q)\} \] as a function of $q$.
Next, the work of Gruber and Holzer (2007) gives an upper bound for the
nondeterministic state complexity of finite languages contained in $B_n$, which
we strengthen using our methods.
Finally, we give some theoretical and experimental results on the dependence
on $n$ of the VC dimension and testing dimension of $NFA_2(q)\cap B_n$.
Related papers
- LevAttention: Time, Space, and Streaming Efficient Algorithm for Heavy Attentions [54.54897832889028]
We show that for any $K$, there is a universal set" $U subset [n]$ of size independent of $n$, such that for any $Q$ and any row $i$, the large attention scores $A_i,j$ in row $i$ of $A$ all have $jin U$.
We empirically show the benefits of our scheme for vision transformers, showing how to train new models that use our universal set while training as well.
arXiv Detail & Related papers (2024-10-07T19:47:13Z) - The Approximate Degree of DNF and CNF Formulas [95.94432031144716]
For every $delta>0,$ we construct CNF and formulas of size with approximate degree $Omega(n1-delta),$ essentially matching the trivial upper bound of $n.
We show that for every $delta>0$, these models require $Omega(n1-delta)$, $Omega(n/4kk2)1-delta$, and $Omega(n/4kk2)1-delta$, respectively.
arXiv Detail & Related papers (2022-09-04T10:01:39Z) - When Variable-Length Codes Meet the Field of Error Detection [0.0]
In the spirit of citeJK97,N21, the error detection-correction capability of variable-length codes can be expressed in term of conditions over $tau_d,k$.
We examine whether those conditions are decidable for a given regular code.
arXiv Detail & Related papers (2022-08-31T08:14:28Z) - Exponential Separation between Quantum and Classical Ordered Binary
Decision Diagrams, Reordering Method and Hierarchies [68.93512627479197]
We study quantum Ordered Binary Decision Diagrams($OBDD$) model.
We prove lower bounds and upper bounds for OBDD with arbitrary order of input variables.
We extend hierarchy for read$k$-times Ordered Binary Decision Diagrams ($k$-OBDD$) of width.
arXiv Detail & Related papers (2022-04-22T12:37:56Z) - Matrix hypercontractivity, streaming algorithms and LDCs: the large
alphabet case [5.88864611435337]
We prove a hypercontractive inequality for matrix-valued functions defined over large alphabets.
We show that every streaming algorithm in the adversarial model achieving a $(r-varepsilon)$-approximation requires $Omega(n1-2/t)$ quantum space.
arXiv Detail & Related papers (2021-09-06T16:56:19Z) - Gray Cycles of Maximum Length Related to k-Character Substitutions [0.0]
Given a word binary relation $tau$ we define a $tau$-Gray cycle over a finite language $X$ to be a permutation $left(w_[i]right)_0le ile |X|-1$ of $X$.
We compute the bound $lambda(n)$ for all cases of the alphabet cardinality and the argument $n$.
arXiv Detail & Related papers (2021-08-31T07:49:15Z) - Quantum speedups for dynamic programming on $n$-dimensional lattice
graphs [0.11470070927586015]
We show a quantum algorithm with complexity $widetilde O(T_Dn)$, where $T_D D+1$.
While the best known classical algorithm is $textpoly(m,n)log n T_Dn$, the time complexity of our quantum algorithm is $textpoly(m,n)log n T_Dn$.
arXiv Detail & Related papers (2021-04-29T14:50:03Z) - Binary strings of finite VC dimension [0.0]
In this paper we investigate subsets named by a predicate $P$ such that the relation $P(x+y)$ has finite VC dimension.
We prove that strings of bounded VC dimension are meagre in the topology of the reals, provide simple rules for bounding the VC dimension of a string, and show that the bi-infinite strings of VC dimension $d$ are a non-so shift space.
arXiv Detail & Related papers (2021-01-16T17:51:52Z) - RNNs can generate bounded hierarchical languages with optimal memory [113.73133308478612]
We show that RNNs can efficiently generate bounded hierarchical languages that reflect the scaffolding of natural language syntax.
We introduce Dyck-($k$,$m$), the language of well-nested brackets (of $k$ types) and $m$-bounded nesting depth.
We prove that an RNN with $O(m log k)$ hidden units suffices, an exponential reduction in memory, by an explicit construction.
arXiv Detail & Related papers (2020-10-15T04:42:29Z) - An Optimal Separation of Randomized and Quantum Query Complexity [67.19751155411075]
We prove that for every decision tree, the absolute values of the Fourier coefficients of a given order $ellsqrtbinomdell (1+log n)ell-1,$ sum to at most $cellsqrtbinomdell (1+log n)ell-1,$ where $n$ is the number of variables, $d$ is the tree depth, and $c>0$ is an absolute constant.
arXiv Detail & Related papers (2020-08-24T06:50:57Z) - Agnostic Q-learning with Function Approximation in Deterministic
Systems: Tight Bounds on Approximation Error and Sample Complexity [94.37110094442136]
We study the problem of agnostic $Q$-learning with function approximation in deterministic systems.
We show that if $delta = Oleft(rho/sqrtdim_Eright)$, then one can find the optimal policy using $Oleft(dim_Eright)$.
arXiv Detail & Related papers (2020-02-17T18:41:49Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.