The notion of abstraction repeatedly appears, in various ways, at all levels of computer science. It involves the aspects of leaving out details and comprehending concepts and mechanisms. It also involves the aspect o...
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ISBN:
(纸本)9781450346986
The notion of abstraction repeatedly appears, in various ways, at all levels of computer science. It involves the aspects of leaving out details and comprehending concepts and mechanisms. It also involves the aspect of recognizing relationships between task elements. The latter aspect was not yet studied with respect to abstraction levels and algorithm design. We study it here. We analyze senior students' algorithmic solutions according to accepted interpretations of multiple abstraction levels, and offer guidelines for enhancing abstraction in students' algorithmics.
We propose a novel classifier for a Recommender System which is based on a Kansei Model in this paper. We called this Recommender System as Kansei Recommender System (hereafter, we denoted as KRS algorithm). The purpo...
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ISBN:
(纸本)9781538672419
We propose a novel classifier for a Recommender System which is based on a Kansei Model in this paper. We called this Recommender System as Kansei Recommender System (hereafter, we denoted as KRS algorithm). The purpose of building KRS algorithm is to reduce the time of training data from database and give more precise recommender items for consumers by considering their Kansei (a Japanese word which means the consumers' psychological feeling). To build a novel classifier, we divide the KRS algorithm into two parts of algorithms: (1) algorithm 1 is proposed to extract Kansei factors (score 1) and evaluation factors (score 2) from consumers' shopping items. (2) algorithm 2 is proposed to give a training dataset that is to fit the scored value of Kansei model. Combining two algorithms, we get a novel classifier for a KRS algorithm. We give an architecture of KRS algorithm based on the database of on-line shopping market in the end of this paper.
Every Boolean function can be presented as a logical formula in conjunctive normal form. Fast algorithm for conjunction plays significant role in overall algorithm for computing arbitrary Boolean function. First, we p...
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ISBN:
(纸本)9783642135224
Every Boolean function can be presented as a logical formula in conjunctive normal form. Fast algorithm for conjunction plays significant role in overall algorithm for computing arbitrary Boolean function. First, we present a quantum query algorithm for conjunction of two bits. Our algorithm uses one quantum query and correct result is obtained with a probability p = 4/5, that improves the previous result. Then, we present the main result - generalization of our approach to design efficient quantum algorithms for computing conjunction of two Boolean functions. Finally, we demonstrate another kind of an algorithm for conjunction of two bits, that has a correct answer probability p = 9/10. This algorithm improves success probability by 10%, but stands aside and cannot be extended to compute conjunction of Boolean functions.
Recently, min-max optimization problems have received increasing attention due to their wide range of applications in machine learning (ML). However, most existing min-max solution techniques are either single-machine...
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ISBN:
(纸本)9781450399265
Recently, min-max optimization problems have received increasing attention due to their wide range of applications in machine learning (ML). However, most existing min-max solution techniques are either single-machine or distributed algorithms coordinated by a central server. In this paper, we focus on the decentralized min-max optimization for learning with domain constraints, where multiple agents collectively solve a nonconvex-strongly-concave min-max saddle point problem without coordination from any server. Decentralized min-max optimization problems with domain constraints underpins many important ML applications, including multi-agent ML fairness assurance, and policy evaluations in multi-agent reinforcement learning. We propose an algorithm called PRECISION (proximal gradient-tracking and stochastic recursive variance reduction) that enjoys a convergence rate of O(1/T), where.. is the maximum number of iterations. To further reduce sample complexity, we propose PRECISION+ with an adaptive batch size technique. We show that the fast O(1/T) convergence of PRECISION and PRECISION+ to an epsilon-stationary point imply O(epsilon(-2)) communication complexity and O(m root n epsilon(-2)) sample complexity, where m is the number of agents and n is the size of dataset at each agent. To our knowledge, this is the first work that achieves O(epsilon(-2)) in both sample and communication complexities in decentralized min-max learning with domain constraints. Our experiments also corroborate the theoretical results.
In this paper we address the problem of symbolic control design of nonlinear control systems with infinite states specifications, modelled by differential equations. An algorithm for the design of symbolic controllers...
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ISBN:
(纸本)9781424477456
In this paper we address the problem of symbolic control design of nonlinear control systems with infinite states specifications, modelled by differential equations. An algorithm for the design of symbolic controllers is presented, which integrates the construction of the discrete abstractions of the plant and of the specification with the design of the controller. This integrated algorithm reduces the space complexity of the control design computations, as formally discussed in the paper and further illustrated through an illustrative example.
Matlab is one of the popular softwares for designing algorithms in scientific researches. Based on the case about calculating similarity matrix, which often occurs in our researches, this paper discusses fast methods ...
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Matlab is one of the popular softwares for designing algorithms in scientific researches. Based on the case about calculating similarity matrix, which often occurs in our researches, this paper discusses fast methods for dealing with large scale data(matrix) from theoretical analysis and algorithm design, and obtains efficient algorithms. By analyzing the case described above, we can develop various abilities of graduate students: mathematical thinking and use, algorithm design. This teaching case can also improve their study and work efficiency.
We study the problem of computing the k maximum sum subsequences. Given a sequence of real numbers (x(1), x(2),..., x(n)) and an integer parameter k, 1 <= k <= 1/2n(n - 1), the problem involves finding the k lar...
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ISBN:
(纸本)9783540241317
We study the problem of computing the k maximum sum subsequences. Given a sequence of real numbers (x(1), x(2),..., x(n)) and an integer parameter k, 1 <= k <= 1/2n(n - 1), the problem involves finding the k largest values of Sigma(j)(l=t) x(l) for 1 <= 1 <= j <= n. The problem for fixed k = 1, also known as the maximum sum subsequence problem, has received much attention in the literature and is linear-time solvable. Recently, Bae and Takaoka presented a Theta (nk)-time algorithm for the k maximum sum subsequences problem. In this paper we design an efficient algorithm that solves the above problem in O(min{k + n log(2) n, n root k}) time in the worst case. Our algorithm is optimal for k = Omega(n log(2) n) and improves over the previously best known result for any value of the user-defined parameter k < 1. Moreover, our results are also extended to the multi-dimensional versions of the k maximum sum subsequences problem;resulting in fast algorithms as well.
Human health is monitored through several physiological measurements such as heart rate, blood pressure, brain activity, etc. These measurements are taken at predefined points in the body and recorded as temporal sign...
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Human health is monitored through several physiological measurements such as heart rate, blood pressure, brain activity, etc. These measurements are taken at predefined points in the body and recorded as temporal signals or colorful images for diagnosis purposes. During the diagnosis, physicians analyze these recordings, sometimes visually, to make treatment decisions. These recordings are usually contaminated with noise caused by different factors such as physiological artifacts or electronic noises of the used electrodes/instruments. Therefore, the pre-processing of these signals and images becomes a crucial need to provide clinicians with useful information to make the right decisions. This Ph. D. work proposes and discusses different biomedical signal processing algorithms and their applications. It develops novel signal/image pre-processing algorithms, based on the Semi-Classical Signal Analysis method (SCSA), to enhance the quality of biomedical signals and images. The SCSA method is based on the decomposition of the input signal or image, using the squared eigenfunctions of a Semi-Classical Schrodinger operator. This approach shows great potential in denoising, and residual water-peak suppression for Magnetic Resonance Spectroscopy (MRS) signals compared to the existing methods. In addition, it shows very promising noise removal, particularly from pulse-shaped signals and from Magnetic Resonance (MR) images. In clinical practice, extracting informative characteristics or features from these pre-processed recordings is very important for advanced analysis and diagnosis. Therefore, new features and proposed are extracted based on the SCSA and fed to machine learning models for smart biomedical diagnosis such as predicting epileptic spikes in Magnetoencephalography (MEG). Moreover, a new Quantization-based Position Weight Matrix (QuPWM) feature extraction method is proposed for other biomedical classifications, such as predicting true Poly(A) regions in a DNA se
We consider the problem of on-line exact string matching of a pattern in a set of highly similar sequences. This can be useful in cases where indexing the sequences is not feasible. We present a preliminary study by r...
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We consider the problem of on-line exact string matching of a pattern in a set of highly similar sequences. This can be useful in cases where indexing the sequences is not feasible. We present a preliminary study by restricting the problem for a specific case where we adapt the classical Morris-Pratt and Knuth-Morris-Pratt algorithms to consider borders with errors. We give an original algorithm for computing borders at Hamming distance 1. We exhibit experimental results showing that our algorithms are much faster than searching for the pattern in each sequences with a very fast on-line exact string matching algorithm.
Train positioning system is the most important part in the operation and control system (OCS) in rail transit system of all kinds, for it can help the OCS system to get the real-time train positioning information and ...
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ISBN:
(纸本)9781509063529
Train positioning system is the most important part in the operation and control system (OCS) in rail transit system of all kinds, for it can help the OCS system to get the real-time train positioning information and to realize fail-safe principle if any incident which may lead to hazard happens. Nowadays, different rail transit system have different ways in realizing train positioning, for the environment of each rail transit lines are different, and there is not a certain method which could be applied to all. Consider that each rail transit line has its own civil construction characteristics, and there is a distance measurement method with the accuracy up to millimeter level based on laser ranging, train positioning can be realized by setting up several sets of laser ranging equipments on-board, collecting ranging data between the train and different civil construction surfaces along the line, and counting the real-time train position out employing these sets of data collected and certain data matching algorithms. In this paper, a train positioning algorithm has been proposed based on inflexion analysis, such algorithm utilizes sets of distance measurement data collected from on-board laser ranging equipments. By setting up an experiment system for train positioning with the aid of laser ranging equipment, the effectiveness of proposed algorithm has been verified.
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