Ryo Yoshinaka

Ryo Yoshinaka
Kyoto University | Kyodai

About

45
Publications
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460
Citations

Publications

Publications (45)
Preprint
Various forms of sorting problems have been studied over the years. Recently, two kinds of sorting puzzle apps are popularized. In these puzzles, we are given a set of bins filled with colored units, balls or water, and some empty bins. These puzzles allow us to move colored units from a bin to another when the colors involved match in some way or...
Chapter
For a graph class \(\mathcal {C}\), the \(\mathcal {C}\)-Edge-Deletion problem asks for a given graph G to delete the minimum number of edges from G in order to obtain a graph in \(\mathcal {C}\). We study the \(\mathcal {C}\)-Edge-Deletion problem for \(\mathcal {C}\) the class of interval graphs and other related graph classes. It follows from Co...
Preprint
For a graph class $\mathcal{C}$, the $\mathcal{C}$-\textsc{Edge-Deletion} problem asks for a given graph $G$ to delete the minimum number of edges from $G$ in order to obtain a graph in $\mathcal{C}$. We study the $\mathcal{C}$-\textsc{Edge-Deletion} problem for $\mathcal{C}$ the permutation graphs, interval graphs, and other related graph classes....
Chapter
This paper considers enumeration of specific subgraphs of a given graph by using a data structure called a zero-suppressed binary decision diagram (ZDD). A ZDD can represent the set of solutions quite compactly. Recent studies have demonstrated that a technique generically called frontier-based search (FBS) is a powerful framework for using ZDDs to...
Article
We propose a general method performed over multivalued decision diagrams that enumerates all subgraphs of an input graph that are characterized by input forbidden induced subgraphs. Our method combines elaborations of classical set operations and the developing construction technique, called the frontier based search, for multivalued decision diagr...
Conference Paper
Several researchers have studied subgraph enumeration algorithms that use a compressed expression for a family of sets, called a zero-suppressed binary decision diagram (ZDD), to solve subgraph optimization problems. We have two representative approaches to manipulate ZDDs effectively. One is fundamental mathematical operations on families of sets...
Conference Paper
We identify the properties of context-free grammars that exactly correspond to the behavior of the dual and primal versions of Clark and Yoshinaka’s distributional learning algorithm and call them the very weak finite context/kernel property. We show that the very weak finite context property does not imply Yoshinaka’s weak finite context property,...
Conference Paper
The token swapping problem (TSP) and its colored version are reconfiguration problems on graphs. This paper is concerned with the complexity of the TSP and two new variants; namely parallel TSP and parallel colored TSP. For a given graph where each vertex has a unique token on it, the TSP requires to find a shortest way to modify a token placement...
Article
The token swapping problem (TSP) and its colored version are reconfiguration problems on graphs. This paper is concerned with the complexity of the TSP and two new variants; namely parallel TSP and parallel colored TSP. For a given graph where each vertex has a unique token on it, the TSP requires to find a shortest way to modify a token placement...
Conference Paper
We study tree-generating almost linear second-order ACGs that admit bounded nonlinearity either on the context side or on the substructure side, and give distributional learning algorithms for them.
Chapter
This chapter reviews recent progress in distributional learning in grammatical inference as applied to learning context-free and multiple context-free grammars. We discuss the basic principles of distributional learning, and present two classes of representations, primal and dual, where primal approaches use nonterminals based on strings or sets of...
Conference Paper
Approaches based on the idea generically called distributional learning have been making great success in the algorithmic learning of context-free languages and their extensions. We in this paper show that conjunctive grammars are also learnable by a distributional learning technique. Conjunctive grammars are context-free grammars enhanced with con...
Article
The manipulation of large sequence data is one of the most important problems in string processing. In this paper, we discuss a new data structure for storing and manipulating sets of strings, called Sequence Binary Decision Diagrams (sequence BDDs), which has recently been introduced by Loekito et al. (2010) as a descendant of both acyclic DFAs (A...
Article
Seki et al. (Theor. Comput. Sci. 88(2):191–229, 1991) showed that every m-multiple context-free language L is weakly 2m-iterative in the sense that either L is finite or L contains a subset of the form \(\{ u_{0} w_{1}^{i} u_{1} \cdots w_{2m}^{i} u_{2m} \mid i \in \mathbb {N}\}\) , where w 1⋯w 2n ≠ε. Whether every m-multiple context-free language L...
Conference Paper
We define an algebraic structure, paired complete idempotent semirings (pcis), which are appropriate for defining a denotational semantics for multiple context-free grammars of dimension 2 (2-mcfg). We demonstrate that homomorphisms of this structure will induce well-behaved morphisms of the grammar, and generalize the syntactic concept lattice fro...
Article
Full-text available
Determining loss minimum configuration in a distribution network is a hard discrete optimization problem involving many variables. Since more and more dispersed generators are installed on the demand side of power systems and they are reconfigured frequently, developing automatic approaches is indispensable for effectively managing a large-scale di...
Article
Full-text available
Link puzzles involve finding paths or a cycle in a grid that satisfy given local and global properties. This paper proposes algorithms that enumerate solutions and instances of two link puzzles, Slitherlink and Numberlink, by zero-suppressed binary decision diagrams (ZDDs). A ZDD is a compact data structure for a family of sets provided with a rich...
Article
In this article, we disprove the long-standing conjecture, proposed by R.E. Bryant in 1986, that his binary decision diagram (BDD) algorithm computes any binary operation on two Boolean functions in linear time in the input–output sizes. We present Boolean functions for which the time required by Bryantʼs algorithm is a quadratic of the input–outpu...
Conference Paper
Recently several "distributional learning algorithms" have been proposed and have made great success in learning different subclasses of context-free grammars. The distributional learning models and exploits the relation between strings and contexts that form grammatical sentences in the language of the learning target. There are two main approache...
Article
Full-text available
We present an algorithm for the inference of some Multi-ple Context-Free Grammars from Membership and Equivalence Queries, using the Minimally Adequate Teacher model of Angluin. This is an ex-tension of the congruence based methods for learning some Context-Free Grammars proposed by Clark (ICGI 2010). We define the natural exten-sion of the syntact...
Conference Paper
Full-text available
Natural languages require grammars beyond context-free for their description. Here we extend a family of distributional learning algorithms for context-free grammars to the class of Parallel Multiple Context-Free Grammars (pmcfgs). These grammars have two additional operations beyond the simple context-free operation of concatenation: the ability t...
Conference Paper
This paper demonstrates how existing distributional learning techniques for context-free grammars can be adapted to simple context-free tree grammars in a straightforward manner once the necessary notions and properties for string languages have been redefined for trees. Distributional learning is based on the decomposition of an object into a subs...
Conference Paper
Full-text available
Angluin (1980) showed that there is a consistent and conservative learner for the class of non-erasing pattern languages; however, most of these learners are NP-hard. In the current work, the complexity of consistent polynomial time learners for the class of non-erasing pattern languages is revisited, with the goal to close one gap left by Angluin,...
Conference Paper
Recent studies on grammatical inference have demonstrated the benefits of "distributional learning" for learning context-free and context-sensitive languages. Distributional learning models and exploits the relation between strings and contexts in the language of the learning target. There are two main approaches. One, which we call primal, constru...
Conference Paper
Minimalist grammars (MGs) constitute a mildly context-sensitive formalism when being equipped with a particular locality condition (LC), the shortest move condition. In this format MGs define the same class of derivable string languages as multiple context-free grammars (MCFGs). Adding another LC to MGs, the specifier island condition (SPIC), resul...
Conference Paper
Recent studies on grammatical inference have demonstrated the benefits of the learning strategy called “distributional learning” for context-free and multiple context-free languages. This paper gives a comprehensive view of distributional learning of “context-free” formalisms (roughly in the sense of Courcelle 1987) in terms of abstract categorial...
Article
Recently Clark and Eyraud (2007) [10] have shown that substitutable context-free languages, which capture an aspect of natural language phenomena, are efficiently identifiable in the limit from positive data. Generalizing their work, this paper presents a polynomial-time learning algorithm for new subclasses of multiple context-free languages with...
Conference Paper
This paper presents an efficient algorithm that identifies a rich subclass of multiple context-free languages in the limit from positive data and membership queries by observing where each tuple of strings may occur in sentences of the language of the learning target. Our technique is based on A. Clark et al.’s work in [Lect. Notes Comput. Sci. 527...
Conference Paper
It is a well-known theorem by Chomsky and Schützenberger (1963) that every context-free language can be represented as a homomorphic image of the intersection of a Dyck language and a regular language. This paper gives a Chomsky-Schützenberger-type characterization for multiple context-free languages, which are a natural extension of context-free l...
Conference Paper
Recently Clark and Eyraud (2007) have shown that substitutable context-free languages, which capture an aspect of natural language phenomena, are efficiently identifiable in the limit from positive data. Generalizing their work, this paper presents a polynomial-time learning algorithm for new subclasses of mildly context-sensitive languages with va...
Article
Greibach normal form (GNF) introduced by Greibach, which facilitates proving several properties of context-free languages, is studied. Double Greibach normal form is a variant of GNF, where the right-hand side of each production begins and ends with a terminal symbol. Engelfriet has given an elementary proof of double GNF, while Rosenkrantz's and H...
Conference Paper
Recently Clark and Eyraud (2005, 2007) have shown that substitutable context-free languages are polynomial-time identifiable in the limit from positive data. Substitutability in context-free languages can be thought of as the analogue of reversibility in regular languages. While reversible languages admit a hierarchy, namely k-reversible regular la...
Conference Paper
This paper presents an efficient algorithm solving the inclusion problem of a new subclass of context-free languages. The languages are accepted by the special kind of real-time deterministic pushdown automata, called strongly forward-deterministic pushdown automata, that go to the same state and push the same sequence of stack symbols whenever tra...
Chapter
In this chapter, we presented two new notions. One is an extension of episodic finite-state MDPs from the point of view of grammatical formalism. We can extend well-known methods of reinforcement learning and apply them to this extension easily. The other is the probabilistic generalities of grammars and unifiability of them. This notion plays an i...
Conference Paper
The class of very simple grammars is known to be polynomial-time identifiable in the limit from positive data. This paper gives even more general discussion on the efficiency of identification of very simple grammars from positive data, which includes both positive and negative results. In particular, we present an alternative efficient inconsisten...
Conference Paper
The abstract categorial grammars (ACGs, for short) are a type-theoretic grammatical formalism intended for the description of natural languages [1]. It is based on the implicative fragment of multiplicative linear logic, which results in a rather simple framework.
Conference Paper
The class of very simple grammars is known to be polynomial-time identifiable in the limit from positive data. This paper gives an even more general discussion on the efficiency of identification of very simple grammars from positive data, which includes both positive and negative results. In particular, we present an alternative efficient inconsis...
Conference Paper
Recently, some non-regular subclasses of context-free grammars have been found to be efficiently learnable from positive data. In order to use these efficient algorithms to infer probabilistic languages, one must take into account not only equivalences between languages but also probabilistic generalities of grammars. The probabilistic generality o...
Conference Paper
The class of very simple grammars is known to be polynomial-time identifiable in the limit from positive data. This paper introduces an extension of very simple grammars called right-unique simple grammars, and presents an algorithm that identifies right-unique simple grammars in the limit from positive data. The learning algorithm possesses the fo...
Article
Abstract We use techniques familiar from the theory of context-free gram- mars to show that, given a second-order abstract categorial grammar (ACG), one can eectively find a lexicalized second-order ACG whose object language is the object language of the original ACG minus com- binators.
Conference Paper
Previous studies have shown that some well-known classes of grammars can be simulated by Abstract Categorial Grammars (de Groote 2001) in straightforward ways. These classes of grammars all generate subclasses of the PTIME languages. While the exact generative capacity of the class of ACGs and the complexity of its universal membership problem are...
Conference Paper
A lambda term is linear if every bound variable occurs exactly once. The same constant may occur more than once in a linear term. It is known that higher-order matching in the linear lambda calculus is NP-complete (de Groote 2000), even if each unknown occurs exactly once (Salvati and de Groote 2003). Salvati and de Groote (2003) also claim that th...
Article
The abstract categorial grammar (ACG) is a grammar formalism based on linear lambda calculus. It is natural to ask how the expressive power of ACGs increases when we relax the linearity constraint on the formalism. This paper introduces the notion of affi ne ACGs by extending the definition of original ACGs, and pres ents a procedure for converting...

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