Search results for "oftware"
showing 10 items of 7396 documents
Stability-Based Model Selection for High Throughput Genomic Data: An Algorithmic Paradigm
2012
Clustering is one of the most well known activities in scien- tific investigation and the object of research in many disciplines, ranging from Statistics to Computer Science. In this beautiful area, one of the most difficult challenges is the model selection problem, i.e., the identifi- cation of the correct number of clusters in a dataset. In the last decade, a few novel techniques for model selection, representing a sharp departure from previous ones in statistics, have been proposed and gained promi- nence for microarray data analysis. Among those, the stability-based methods are the most robust and best performing in terms of predic- tion, but the slowest in terms of time. Unfortunately…
Debates with Small Transparent Quantum Verifiers
2014
We study a model where two opposing provers debate over the membership status of a given string in a language, trying to convince a weak verifier whose coins are visible to all. We show that the incorporation of just two qubits to an otherwise classical constant-space verifier raises the class of debatable languages from at most NP to the collection of all Turing-decidable languages (recursive languages). When the verifier is further constrained to make the correct decision with probability 1, the corresponding class goes up from the regular languages up to at least E.
The PASSI and Agile PASSI MAS Meta-models Compared with a Unifying Proposal
2005
A great number of processes for multi-agent systems design have been presented in last years to support the different approaches to agent-oriented design; each process is specific for a particular class of problems and it instantiates a specific MAS meta-model. These differences produce inconsistences and overlaps: a MAS meta-model may define a term not referred by another, or the same term can be used with a different meaning. We think that the lack of a standardization may cause a significant delay to the diffusion of the agent paradigm outside research context. Working for this unification goal, it is also necessary to define in unambiguous way the terms of the agent model and their rela…
A Methodology to Detect Temporal Regularities in User Behavior for Anomaly Detection
2001
Network security, and intrusion detection in particular, represents an area of increased in security community over last several years. However, the majority of work in this area has been concentrated upon implementation of misuse detection systems for intrusion patterns monitoring among network traffic. In anomaly detection the classification was mainly based on statistical or sequential analysis of data often neglect ion temporal events' information as well as existing relations between them. In this paper we consider an anomaly detection problem as one of classification of user behavior in terms of incoming multiple discrete sequences. We present and approach that allows creating and mai…
One-Sided Prototype Selection on Class Imbalanced Dissimilarity Matrices
2012
In the dissimilarity representation paradigm, several prototype selection methods have been used to cope with the topic of how to select a small representation set for generating a low-dimensional dissimilarity space. In addition, these methods have also been used to reduce the size of the dissimilarity matrix. However, these approaches assume a relatively balanced class distribution, which is grossly violated in many real-life problems. Often, the ratios of prior probabilities between classes are extremely skewed. In this paper, we study the use of renowned prototype selection methods adapted to the case of learning from an imbalanced dissimilarity matrix. More specifically, we propose the…
On Duality in Learning and the Selection of Learning Teams
1996
AbstractPrevious work in inductive inference dealt mostly with finding one or several machines (IIMs) that successfully learn collections of functions. Herein we start with a class of functions and considerthe learner setof all IIMs that are successful at learning the given class. Applying this perspective to the case of team inference leads to the notion ofdiversificationfor a class of functions. This enable us to distinguish between several flavours of IIMs all of which must be represented in a team learning the given class.
A family of experiments to generate graphical user interfaces from BPMN models with stereotypes
2021
Abstract Context: A significant gap separates Business Process Model and Notation (BPMN) models representing processes from the design of Graphical User Interfaces (GUIs). Objective: This paper reports on a family of experiments to validate a method to automatically generate GUIs from BPMN models using stereotypes complemented with UML class primitives, and transformation rules. Method: We conducted two replications (23 and 31 subjects respectively) in which we compared two methods to generate GUIs from BPMN models; one automatic (using Stereotyped BPMN models) and one manual (using Non-stereotyped BPMN models). The study focuses on comparing effort, accuracy, and satisfaction (in terms of …
Evaluative linguistic expressions vs. fuzzy categories
2015
In this paper, we discuss the distinction between categories characterized by verbal labels taken from a fuzzy rating scale and special class of linguistic expressions, called evaluative. The latter form a general class of expressions that includes gradable and evaluative adjectives and their hedges. First, we will provide a brief linguistic analysis of them. Then we outline basic principles for construction of the mathematical model of semantics of evaluative expressions. In Section 3 we will analyze the concepts of rating scale with verbal labels (fuzzy rating scale), their semantics and demonstrate that the latter cannot be identified with the semantics of evaluative expressions. Finally…
Noise-tolerant efficient inductive synthesis of regular expressions from good examples
1997
We present an almost linear time method of inductive synthesis restoring simple regular expressions from one representative (good) example. In particular, we consider synthesis of expressions of star-height one, where we allow one union operation under each iteration, and synthesis of expressions without union operations from examples that may contain mistakes. In both cases we provide sufficient conditions defining precisely the class of target expressions and the notion of good examples under which the synthesis algorithm works correctly, and present the proof of correctness. In the case of expressions with unions the proof is based on novel results in the combinatorics of words. A genera…
Stochastic Stability Analysis for Markovian Jump Neutral Nonlinear Systems
2012
In this paper, the stability problem is studied for a class of Markovian jump neutral nonlinear systems with time-varying delay. By Lyapunov-Krasovskii function approach, a novel mean-square exponential stability criterion is derived for the situations that the system's transition rates are completely accessible, partially accessible and non-accessible, respectively. Moreover, the developed stability criterion is extended to the systems with different bounded sector nonlinear constraints. Finally, some numerical examples are provided to illustrate the effectiveness of the proposed methods.