Search results for " Mach"
showing 10 items of 1388 documents
Positive Versions of Polynomial Time
1998
Abstract We show that restricting a number of characterizations of the complexity class P to be positive (in natural ways) results in the same class of (monotone) problems, which we denote by posP . By a well-known result of Razborov, posP is a proper subclass of the class of monotone problems in P . We exhibit complete problems for posP via weak logical reductions, as we do for other logically defined classes of problems. Our work is a continuation of research undertaken by Grigni and Sipser, and subsequently Stewart; indeed, we introduce the notion of a positive deterministic Turing machine and consequently solve a problem posed by Grigni and Sipser.
On a class of languages with holonomic generating functions
2017
We define a class of languages (RCM) obtained by considering Regular languages, linear Constraints on the number of occurrences of symbols and Morphisms. The class RCM presents some interesting closure properties, and contains languages with holonomic generating functions. As a matter of fact, RCM is related to one-way 1-reversal bounded k-counter machines and also to Parikh automata on letters. Indeed, RCM is contained in L-NFCM but not in L-DFCM, and strictly includes L-CPA. We conjecture that L-DFCM subset of RCM
Learning Molecular Classes from Small Numbers of Positive Examples Using Graph Grammars
2021
We consider the following problem: A researcher identified a small number of molecules with a certain property of interest and now wants to find further molecules sharing this property in a database. This can be described as learning molecular classes from small numbers of positive examples. In this work, we propose a method that is based on learning a graph grammar for the molecular class. We consider the type of graph grammars proposed by Althaus et al. [2], as it can be easily interpreted and allows relatively efficient queries. We identify rules that are frequently encountered in the positive examples and use these to construct a graph grammar. We then classify a molecule as being conta…
A new paradigm for pattern classification: Nearest Border Techniques
2013
Published version of a chapter in the book: AI 2013: Advances in Artificial Intelligence. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-319-03680-9_44 There are many paradigms for pattern classification. As opposed to these, this paper introduces a paradigm that has not been reported in the literature earlier, which we shall refer to as the Nearest Border (NB) paradigm. The philosophy for developing such a NB strategy is as follows: Given the training data set for each class, we shall first attempt to create borders for each individual class. After that, we advocate that testing is accomplished by assigning the test sample to the class whose border it lies closest to…
Models of Computation, Riemann Hypothesis, and Classical Mathematics
1998
Classical mathematics is a source of ideas used by Computer Science since the very first days. Surprisingly, there is still much to be found. Computer scientists, especially, those in Theoretical Computer Science find inspiring ideas both in old notions and results, and in the 20th century mathematics. The latest decades have brought us evidence that computer people will soon study quantum physics and modern biology just to understand what computers are doing.
Variability of Classification Results in Data with High Dimensionality and Small Sample Size
2021
The study focuses on the analysis of biological data containing information on the number of genome sequences of intestinal microbiome bacteria before and after antibiotic use. The data have high dimensionality (bacterial taxa) and a small number of records, which is typical of bioinformatics data. Classification models induced on data sets like this usually are not stable and the accuracy metrics have high variance. The aim of the study is to create a preprocessing workflow and a classification model that can perform the most accurate classification of the microbiome into groups before and after the use of antibiotics and lessen the variability of accuracy measures of the classifier. To ev…
Comparative analysis of architectures for monitoring cloud computing infrastructures
2015
The lack of control over the cloud resources is one of the main disadvantages associated to cloud computing. The design of efficient architectures for monitoring such resources can help to overcome this problem. This contribution describes a complete set of architectures for monitoring cloud computing infrastructures, and provides a taxonomy of them. The architectures are described in detail, compared among them, and analysed in terms of performance, scalability, usage of resources, and security capabilities. The architectures have been implemented in real world settings and empirically validated against a real cloud computing infrastructure based on OpenStack. More than 1000 virtual machin…
Gödel and the Blind Watchmaker
2015
While accepting that contingency is key to biological evolution, we wonder how much need there is for it. It is extremely difficult to talk about trends in evolution, but the fact remains that they are found here and there when evolutionary experiments are repeated. But we should ask, for example, whether there is an unavoidable tendency of life towards progressive complexity . This chapter deals with certain theoretical considerations from Logic and Computing on the conditions necessary to formulate a predictive evolutionary theory .
LR(k) Parsing
1990
In this chapter we shall generalize the notion of strong LL(k) parsing presented in Chapter 5 and consider a method for deterministic left parsing that applies to a slightly wider class of context-free grammars than does the strong LL(k) parsing method. This method will be called “canonical LL(k) parsing”. As in strong LL(k) parsing, the acronym “LL(k)” means that the input string is parsed (1) in a single Left-to-right scan, (2) producing a Left parse, and (3) using lookahead of length k.
Ambainis-Freivalds’ Algorithm for Measure-Once Automata
2001
An algorithm given by Ambainis and Freivalds [1] constructs a quantum finite automaton (QFA) with O(log p) states recognizing the language Lp = {ai| i is divisible by p} with probability 1 - Ɛ , for any Ɛ > 0 and arbitrary prime p. In [4] we gave examples showing that the algorithm is applicable also to quantum automata of very limited size. However, the Ambainis-Freivalds algoritm is tailored to constructing a measure-many QFA (defined by Kondacs andWatrous [2]), which cannot be implemented on existing quantum computers. In this paper we modify the algorithm to construct a measure-once QFA of Moore and Crutchfield [3] and give examples of parameters for this automaton. We show for the lang…