Paths and trails in edge-colored graphs

This paper deals with the existence and search for properly edge-colored paths/trails between two, not necessarily distinct, vertices s$s$ and t$t$ in an edge-colored graph from an algorithmic perspective. First we show that several versions of the s−t$s-t$ path/trail problem have polynomial solutions including the shortest path/trail case. We give polynomial algorithms for finding a longest properly edge-colored path/trail between s$s$ and t$t$ for a particular class of graphs and characterize edge-colored graphs without properly edge-colored closed trails. Next, we prove that deciding whether there exist k$k$ pairwise vertex/edge disjoint properly edge-colored s−t$s-t$ paths/trails in a c$c$-edge-colored graph G^c$G^c$ is NP-complete even for k=2$k=2$ and c=Ω(n²)$c=\Omega \left(n^2\right)$, where n$n$ denotes the number of vertices in G^c$G^c$. Moreover, we prove that these problems remain NP-complete for c$c$-edge-colored graphs containing no properly edge-colored cycles and c=Ω(n)$c=\Omega \left(n\right)$. We obtain some approximation results for those maximization problems together with polynomial results for some particular classes of edge-colored graphs.     

Divergence bounded computable real numbers

A real x$x$ is called h$h$-bounded computable  , for some function h:N→N$h:\mathbb{N}\to \mathbb{N}$, if there is a computable sequence (_xs)$(x_s)$ of rational numbers which converges to x$x$ such that, for any n∈N$n\in \mathbb{N}$, at most h(n)$h(n)$ non-overlapping pairs of its members are separated by a distance larger than 2^-n$2^{-n}$. In this paper we discuss properties of h$h$-bounded computable reals for various functions h$h$. We will show a simple sufficient condition for a class of functions h$h$ such that the corresponding h$h$-bounded computable reals form an algebraic field. A hierarchy theorem for h$h$-bounded computable reals is also shown. Besides we compare semi-computability and weak computability with the h$h$-bounded computability for special functions h$h$.     

Large independent sets in random regular graphs

We present algorithmic lower bounds on the size _sd$s_d$ of the largest independent sets of vertices in random d$d$-regular graphs, for each fixed d≥3$d\ge 3$. For instance, for d=3$d=3$ we prove that, for graphs on n$n$ vertices, _sd≥0.43475n$s_d\ge 0.43475n$ with probability approaching one as n$n$ tends to infinity.     

Optimal lower bounds for rank and select indexes

We develop a new lower bound technique for data structures. We show an optimal Ω(nlglgn/lgn)$\Omega (nlglgn/lgn)$ space lower bounds for storing an index that allows to implement rank and select queries on a bit vector B$B$ provided that B$B$ is stored explicitly. These results improve upon [Peter Bro Miltersen, Lower bounds on the size of selection and rank indexes, in: Proceedings of the 16th Annual ACM–SIAM Symposium on Discrete Algorithms, 2005, pp. 11–12]. We show Ω((m/t)lgt)$\Omega ((m/t)lgt)$ lower bounds for storing rank/select index in the case where B$B$ has m$m$ 1$1$-bits in it and the algorithm is allowed to probe t$t$ bits of B$B$. We also present an improved data structure that implements both rank and select queries with an index of size (1+o(1))(nlglgn/lgn)+O(n/lgn)$(1+o\left(1\right))(nlglgn/lgn)+O(n/lgn)$, that is, compared to existing results we give an explicit constant for storage in the RAM model with word size lgn$lgn$. An advantage of this data structure is that both rank and select indexes share the most space consuming part of order Θ(nlglgn/lgn)$\Theta (nlglgn/lgn)$ making it more practical for implementation.     

Efficient enumeration of words in regular languages

The cross-section enumeration problem is to list all words of length n$n$ in a regular language L$L$ in lexicographical order. The enumeration problem is to list the first m$m$ words in L$L$ according to radix order. We present an algorithm for the cross-section enumeration problem that is linear in n+t$n+t$, where t$t$ is the output size. We provide a detailed analysis of the asymptotic running time of our algorithm and that of known algorithms for both enumeration problems. We discuss some shortcomings of the enumeration algorithm found in the Grail computation package. In the practical domain, we modify Mäkinen’s enumeration algorithm to get an algorithm that is usually the most efficient in practice. We performed an extensive performance analysis of the new and previously known enumeration and cross-section enumeration algorithms and found when each algorithm is preferable.     

Learning multiple languages in groups

We consider a variant of Gold’s learning paradigm where a learner receives as input n$n$ different languages (in the form of one text where all input languages are interleaved). Our goal is to explore the situation when a more “coarse” classification of input languages is possible, whereas more refined classification is not. More specifically, we answer the following question: under which conditions, a learner, being fed n$n$ different languages, can produce m$m$ grammars covering all input languages, but cannot produce k$k$ grammars covering input languages for any k>m$k>m$. We also consider a variant of this task, where each of the output grammars may not cover more than r$r$ input languages. Our main results indicate that the major factor affecting classification capabilities is the difference n−m$n-m$ between the number n$n$ of input languages and the number m$m$ of output grammars. We also explore the relationship between classification capabilities for smaller and larger groups of input languages. For the variant of our model with the upper bound on the number of languages allowed to be represented by one output grammar, for classes consisting of disjoint languages, we found complete picture of relationship between classification capabilities for different parameters n$n$ (the number of input languages), m$m$ (number of output grammars), and r$r$ (bound on the number of languages represented by each output grammar). This picture includes a combinatorial characterization of classification capabilities for the parameters n,m,r$n,m,r$ of certain types.     

Spanners for bounded tree-length graphs

This paper concerns construction of additive stretched spanners with few edges for n$n$-vertex graphs having a tree-decomposition into bags of diameter at most δ$\delta$, i.e., the tree-length δ$\delta$ graphs. For such graphs we construct additive 2δ$2\delta$-spanners with O(δn+nlogn)$O(\delta n+nlogn)$ edges, and additive 4δ$4\delta$-spanners with O(δn)$O\left(\delta n\right)$ edges. This provides new upper bounds for chordal graphs for which δ=1$\delta =1$. We also show a lower bound, and prove that there are graphs of tree-length δ$\delta$ for which every multiplicative δ$\delta$-spanner (and thus every additive (δ−1)$(\delta -1)$-spanner) requires Ω(n^1+1/Θ(δ))$\Omega \left(n^{1+1/\Theta \left(\delta \right)}\right)$ edges.     

Conjunctive query evaluation by search-tree revisited

The most natural and perhaps most frequently used method for testing membership of an individual tuple in a conjunctive query is based on searching trees of partial solutions, or search-trees. We investigate the question of evaluating conjunctive queries with a time-bound guarantee that is measured as a function of the size of the optimal search-tree. We provide an algorithm that, given a database D$D$, a conjunctive query Q$Q$, and a tuple a$a$, tests whether Q(a)$Q\left(a\right)$ holds in D$D$ in time bounded by a polynomial in (sn)^logk(sn)^loglogn${\left(sn\right)}^{logk}{\left(sn\right)}^{loglogn}$ and n^r$n^r$, where n$n$ is the size of the domain of the database, k$k$ is the number of bound variables of the conjunctive query, s$s$ is the size of the optimal search-tree, and r$r$ is the maximum arity of the relations. In many cases of interest, this bound is significantly smaller than the n^O(k)$n^{O\left(k\right)}$ bound provided by the naive search-tree method. Moreover, our algorithm has the advantage of guaranteeing the bound for any given conjunctive query. In particular, it guarantees the bound for queries that admit an equivalent form that is much easier to evaluate, even when finding such a form is an NP-hard task. Concrete examples include the conjunctive queries that can be non-trivially folded into a conjunctive query of bounded size or bounded treewidth. All our results translate to the context of constraint-satisfaction problems via the well-publicized correspondence between both frameworks.     

The number of roots of a lacunary bivariate polynomial on a line

We prove that a polynomial f∈R[x,y]$f\in \mathbb{R}[x,y]$ with t$t$ non-zero terms, restricted to a real line y=ax+b$y=ax+b$, either has at most 6t−4$6t-4$ zeros or vanishes over the whole line. As a consequence, we derive an alternative algorithm for deciding whether a linear polynomial y−ax−b∈K[x,y]$y-ax-b\in K[x,y]$ divides a lacunary polynomial f∈K[x,y]$f\in K[x,y]$, where K$K$ is a real number field. The number of bit operations performed by the algorithm is polynomial in the number of non-zero terms of f$f$, in the logarithm of the degree of f$f$, in the degree of the extension K/Q$K/\mathbb{Q}$ and in the logarithmic height of a$a$, b$b$ and f$f$.     

Algorithms for near solutions to polynomial equations

Let F(x,y)$F(x,y)$ be a polynomial over a field K$K$ and m$m$ a nonnegative integer. We call a polynomial g$g$ over K$K$ an m$m$-near solution of F(x,y)$F(x,y)$ if there exists a c∈K$c\in K$ such that F(x,g)=cx^m$F(x,g)=c{x}^m$, and the number c$c$ is called an m$m$-value of F(x,y)$F(x,y)$ corresponding to g$g$. In particular, c$c$ can be 0. Hence, by viewing F(x,y)=0$F(x,y)=0$ as a polynomial equation over K[x]$K\left[x\right]$ with variable y$y$, every solution of the equation F(x,y)=0$F(x,y)=0$ in K[x]$K\left[x\right]$ is also an m$m$-near solution. We provide an algorithm that gives all m$m$-near solutions of a given polynomial F(x,y)$F(x,y)$ over K$K$, and this algorithm is polynomial time reducible to solving one variable equations over K$K$. We introduce approximate solutions to analyze the algorithm. We also give some interesting properties of approximate solutions.     

Expanders and time-restricted branching programs

The replication number   of a branching program is the minimum number R$R$ such that along every accepting computation at most R$R$ variables are tested more than once; the sets of variables re-tested along different computations may be different. For every branching program, this number lies between 0$0$ (read-once programs) and the total number n$n$ of variables (general branching programs). The best results so far were exponential lower bounds on the size of branching programs with R=o(n/logn)$R=o(n/logn)$. We improve this to R≤?n$R\le ?n$ for a constant ?>0$?>0$. This also gives an alternative and simpler proof of an exponential lower bound for (1+?)n$(1+?)n$ time branching programs for a constant ?>0$?>0$. We prove these lower bounds for quadratic functions of Ramanujan graphs.     

Non-reducible descriptions for conditional Kolmogorov complexity

Assume that a program p$p$ on input a$a$ outputs b$b$. We are looking for a shorter program q$q$ having the same property (q(a)=b$q\left(a\right)=b$). In addition, we want q$q$ to be simple conditional to p$p$ (this means that the conditional Kolmogorov complexity K(q|p)$K\left(q\right|p)$ is negligible). In the present paper, we prove that sometimes there is no such program q$q$, even in the case when the complexity of p$p$ is much bigger than K(b|a)$K\left(b\right|a)$. We give three different constructions that use the game approach, probabilistic arguments and algebraic arguments, respectively.     

Origami fold as algebraic graph rewriting

We formalize paper fold (origami) by graph rewriting. Origami construction is abstractly described by a rewriting system (O,?)$(\mathbb{O},?)$, where O$\mathbb{O}$ is the set of abstract origamis and ?$?$ is a binary relation on O$\mathbb{O}$, that models fold  . An abstract origami is a structure (Π,∽,?)$(\Pi ,\backsim ,?)$, where Π$\Pi$ is a set of faces constituting an origami, and ∽$\backsim$ and ?$?$ are binary relations on Π$\Pi$, each representing adjacency and superposition relations between the faces.     

Efficient pebbling for list traversal synopses with application to program rollback

We show how to support efficient back traversal in a unidirectional list, using small memory and with essentially no slowdown in forward steps. Using O(lgn)$O(lgn)$ memory for a list of size n$n$, the i$i$’th back-step from the farthest point reached so far takes O(lgi)$O(lgi)$ time in the worst case, while the overhead per forward step is at most ?$?$ for arbitrary small constant ?>0$?>0$. An arbitrary sequence of forward and back steps is allowed. A full trade-off between memory usage and time per back-step is presented: k$k$ vs. kn^1/k$k{n}^{1/k}$ and vice versa. Our algorithms are based on a novel pebbling technique which moves pebbles on a virtual binary, or n^1/k$n^{1/k}$-ary, tree that can only be traversed in a pre-order fashion.