In this paper, we study data-driven chance constrained stochastic programs, or more
specifically, stochastic programs with distributionally robust chance constraints (DCCs) in a …

The problem of inducing, learning or inferring grammars has been studied for decades, but
only in recent years has grammatical inference emerged as an independent field with …

话题检测与跟踪是一项面向新闻媒体信息流进行未知话题识别和已知话题跟踪的信息处理技术.
自从1996 年前瞻性的探索以来, 该领域进行的多次大规模评测为信息识别 …

The field of grammatical inference (also known as grammar induction) is transversal to a
number of research areas including machine learning, formal language theory, syntactic and …

This article presents an overview of Probabilistic Automata (PA) and discrete Hidden Markov
Models (HMMs), and aims at clarifying the links between them. The first part of this work …

The proliferation of online information sources has led to an increased use of wrappers for
extracting data from Web sources. While most of the previous research has focused on quick …

We present an algorithm for reconstruction of a probabilistic deterministic finite automaton
(PDFA) from a given black-box language model, such as a recurrent neural network (RNN) …

Probabilistic finite-state machines are used today in a variety of areas in pattern recognition
or in fields to which pattern recognition is linked. In part I of this paper, we surveyed these …

A tailored model of a system is the prerequisite for various analysis tasks, such as anomaly
detection, fault identification, or quality assurance. This paper deals with the algorithmic …

Vogel-Heuser) erschienen ist, wurde ein wichtiger Schritt unternommen, das Thema
Industrie 4.0 in der Fachliteratur zu verankern. Doch bereits damals war uns als …