The probably approximately correct (PAC) model of learning and its extension to real-valued function classes sets a rigorous framework based upon which the complexity of learning a target from a function class using a finite sample can be computed. There is one main restriction, however, that the function class have a finite VC-dimension or scale-sensitive pseudo-dimension. In this paper we pre...

We propose an extension of Gaussian mixture models in the statistical-mechanical point of view. The conventional Gaussian mixture models are formulated to divide all points in given data to some kinds of classes. We introduce some quantum states constructed by superposing conventional classes in linear combinations. Our extension can provide a new algorithm in classifications of data by means o...

Maintenance is one of the major concerns of software developers and industries. The success of this critical phase depends highly on the changeability of the software. In order to evaluate the flexibility of a software to accommodate changes, we have defined a change impact model for object-oriented systems. As previously defined, it calculates the impacted classes due to an atomic change. In t...

In a recent paper we introduced a new framework for the study of call by need computations. Using elementary tree automata techniques and ground tree transducers we obtained simple decidability proofs for a hierarchy of classes of rewrite systems that are much larger than earlier classes defined using the complicated sequentiality concept. In this paper we study the modularity of membership in ...

The objective of open set recognition (OSR) is to classify the known classes as well unknown when collected samples cannot exhaust all classes. This paper proposes a loss extension that emphasizes features with larger and smaller magnitudes find representations can more effectively separate from Our contributions include: First, we introduce an be incorporated into different functions discrimin...

The paper proposes a novel graphical notion of state-based classes' inheritance. The proposed graphical notion allows generalization, decomposition, structurization and incremental extension of state-based classes' behaviour using inheritance.

Lexical classifications have proved useful in supporting various linguistic and natural language processing (NLP) tasks. The largest verb classification in English is Levin's (1993) work. VerbNet (Kipper-Schuler 2006) the largest computational verb lexicon currently available for English provides detailed syntactic-semantic descriptions of Levin classes. While the classes included are extensive...

Lexical classifications have proved useful in supporting various natural language processing (NLP) tasks. The largest verb classification for English is Levin’s (1993) work which defined groupings of verbs based on syntactic and semantic properties. VerbNet (Kipper et al., 2000; Kipper-Schuler, 2005) – the largest computational verb lexicon currently available for English – provides detailed sy...