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Study Algorithms

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  • Data Structures and Algorithms: Introduction includes Intermediate-level course, Programming and problem solving, Algorithms - method for solving a problem, Data structures - method to store information.

    pdf6p maiyeumaiyeu23 07-12-2016 22 1   Download

  • Moving objects detection and tracking in video stream are basic fundamental and critical tasks in many computer vision applications. We have presented in this paper effectiveness increase of algorithms for moving objects detection and tracking. For this, we use additive minimax similarity function. Background reconstruction algorithm is developed. Moving and tracking objects detection algorithms are modified on the basis of additive minimax similarity function. Results of experiments are presented according to time expenses of the moving object detection and tracking. ...

    pdf9p tuanlocmuido 19-12-2012 51 6   Download

  • Typical algorithms and data structures textbooks are seven or eight hundred pages long, include chapters about software engineering and the programming language used in the book, and include appendices with yet more information about the programming language. Often they include lengthy case studies with tens of pages of specifications and code. Frequently they are hardcover books printed in two colors; sometimes they have sidebars with various sorts of supplementary material.

    pdf197p tuanloc_do 03-12-2012 57 4   Download

  • This paper describes a novel method by which a dialogue agent can learn to choose an optimal dialogue strategy. While it is widely agreed that dialogue strategies should be formulated in terms of communicative intentions, there has been little work on automatically optimizing an agent's choices when there are multiple ways to realize a communicative intention. Our method is based on a combination of learning algorithms and empirical evaluation techniques.

    pdf7p bunrieu_1 18-04-2013 36 4   Download

  • A great deal of work has been done demonstrating the ability of machine learning algorithms to automatically extract linguistic knowledge from annotated corpora. Very little work has gone into quantifying the difference in ability at this task between a person and a machine. This paper is a first step in that direction.

    pdf8p bunrieu_1 18-04-2013 19 4   Download

  • introduction to algorithms second edition provides a comprehensive introduction to the modern study of computeralgorithms. it presents many algorithms and covers them in considerable depth, yetmakes their design and analysis accessible to all levels of readers. we have tried tokeep explanations elementary without sacrificing depth of coverage or mathemati-cal rigor.

    pdf1203p truongdmc 25-11-2016 40 5   Download

  • (bq) until now, studies in network science have been focused on particular relationships that require varied and sometimes-incompatible datasets, which has kept it from being a truly universal discipline. this new approach would remove the need for tedious human-based analysis of different datasets and help researchers spend more time on the qualitative aspects of network science research. computational network science

    pdf69p bautroibinhyen19 02-03-2017 27 4   Download

  • Tham khảo bài viết 'báo cáo " a combination of the identification algorithm and the modal superposition method for feedback active control of incomplete measured systems"', luận văn - báo cáo phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả

    pdf8p tuanlocmuido 19-12-2012 41 3   Download

  • This paper presents a comparative study of five parameter estimation algorithms on four NLP tasks. Three of the five algorithms are well-known in the computational linguistics community: Maximum Entropy (ME) estimation with L2 regularization, the Averaged Perceptron (AP), and Boosting. We also investigate ME estimation with L1 regularization using a novel optimization algorithm, and BLasso, which is a version of Boosting with Lasso (L1) regularization. We first investigate all of our estimators on two re-ranking tasks: a parse selection task and a language model (LM) adaptation task. ...

    pdf8p hongvang_1 16-04-2013 40 3   Download

  • A method for resolving the ellipses that appear in Japanese dialogues is proposed. This method resolves not only the subject ellipsis, but also those in object and other grammatical cases. In this approach, a machine-learning algorithm is used to select the attributes necessary for a resolution. A decision tree is built, and used as the actual ellipsis resolver. The results of blind tests have shown that the proposed method was able to provide a resolution accuracy of 91.7% for indirect objects, and 78.7% for subjects with a verb predicate. ...

    pdf8p bunrieu_1 18-04-2013 41 3   Download

  • We describe a case study in which a memory-based learning algorithm is trained to simultaneously chunk sentences and assign grammatical function tags to these chunks. We compare the algorithm’s performance on this parsing task with varying training set sizes (yielding learning curves) and different input representations. In particular we compare input consisting of words only, a variant that includes word form information for lowfrequency words, gold-standard POS only, and combinations of these. ...

    pdf8p bunmoc_1 20-04-2013 51 3   Download

  • In statistical machine translation, the generation of a translation hypothesis is computationally expensive. If arbitrary wordreorderings are permitted, the search problem is NP-hard. On the other hand, if we restrict the possible word-reorderings in an appropriate way, we obtain a polynomial-time search algorithm. In this paper, we compare two different reordering constraints, namely the ITG constraints and the IBM constraints.

    pdf8p bunbo_1 17-04-2013 29 2   Download

  • In this paper we compare two grammar-based generation algorithms: the Semantic-Head-Driven Generation Algorithm (SHDGA), and the Essential Arguments Algorithm (EAA). Both algorithms have successfully addressed several outstanding problems in grammarbased generation, including dealing with non-monotonic compositionality of representation, left-recursion, deadlock-prone rules, and nondeterminism. We concentrate here on the comparison of selected properties: generality, efficiency, and determinism.

    pdf8p bunmoc_1 20-04-2013 24 2   Download

  • How might one evaluate the In order to take steps towards establishing a methodology for evaluating Natural Language systems, we relative contributions of each of these factors or comconducted a case study. We attempt to evaluate two pare two approaches to the same problem? different approaches to anaphoric processing in disIn order to take steps towards establishing a course by comparing the accuracy and coverage of methodology for doing this type of comparison, we two published algorithms for finding the co-specifiers conducted a case study. ...

    pdf11p bungio_1 03-05-2013 27 2   Download

  • Adaptive Dialogue Systems are rapidly becoming part of our everyday lives. As they progress and adopt new technologies they become more intelligent and able to adapt better and faster to their environment. Research in this field is currently focused on how to achieve adaptation, and particularly on applying Reinforcement Learning (RL) techniques, so a comparative study of the related methods, such as this, is necessary.

    pdf10p bunthai_1 06-05-2013 34 2   Download

  • Introduction to java programming: Chapter 23 - Algorithm Efficiency and Sorting's Objectives is to estimate algorithm efficiency using the Big O notation; understand growth rates and why constants and smaller terms can be ignored in the estimation.

    pdf45p cocacola_17 09-12-2015 36 2   Download

  • The aim of the dissertation is study and propose a new algorithm for solving the optimal problem in nonlinear model predictive control MIMO system.

    pdf28p change01 05-05-2016 24 2   Download

  • (BQ) Present study attempts to model and optimize the complex electrical discharge machining (EDM) process using soft computing techniques. Artificial neural network (ANN) with back propagation algorithm is used to model the process. As the output parameters are conflicting in nature so there is no single combination of cutting parameters, which provides the best machining performance. A multi-objective optimization method, non-dominating sorting genetic algorithm-II is used to optimize the process.

    pdf9p xuanphuongdhts 27-03-2017 24 2   Download

  • In a previous paper [1], the identification algorithm is presented for feedback active controlled systems. However, this method can only be applied to complete measured systems. The aim of this paper is to present a combination of the identification algorithm and the modal superposition method to control the incomplete measured systems. The system response is expanded by modal eigenfunction technique. The external excitation acting on some first modes is identified with a time delay and with a small error depending on the locations of the sensors. ...

    pdf8p tuanlocmuido 19-12-2012 20 1   Download

  • Word alignment using recency-vector based approach has recently become popular. One major advantage of these techniques is that unlike other approaches they perform well even if the size of the parallel corpora is small. This makes these algorithms worth-studying for languages where resources are scarce. In this work we studied the performance of two very popular recency-vector based approaches, proposed in (Fung and McKeown, 1994) and (Somers, 1998), respectively, for word alignment in English-Hindi parallel corpus.

    pdf8p hongvang_1 16-04-2013 47 1   Download

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