Search results for 'Computer algorithms' (try it on Scholar)

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  1. A. P. Ershov & Donald Ervin Knuth (eds.) (1981). Algorithms in Modern Mathematics and Computer Science: Proceedings, Urgench, Uzbek Ssr, September 16-22, 1979. Springer-Verlag.score: 180.0
  2. Jiri Becvar (1971). Review: Robert R. Korfhage, Logic and Algorithms with Applications to the Computer and Information Sciences. [REVIEW] Journal of Symbolic Logic 36 (2):344-346.score: 120.0
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  3. Charles Rackoff (2006). Dietzfelbinger Martin. Primality Testing in Polynomial Time—From Randomized Algorithms to “PRIMES is in P”. Lecture Notes in Computer Science, Vol. 3000. Springer-Verlag, 2004, X+ 147 Pp. [REVIEW] Bulletin of Symbolic Logic 12 (3):494-496.score: 120.0
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  4. W. Dean (forthcoming). Algorithms and the Mathematical Foundations of Computer Science. Notre Dame Journal of Formal Logic.score: 120.0
     
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  5. Michael E. Cuffaro (forthcoming). How-Possibly Explanations in Quantum Computer Science. Philosophy of Science.score: 90.0
    A primary goal of quantum computer science is to find an explanation for the fact that quantum computers are more powerful than classical computers. In this paper I argue that to answer this question is to compare algorithmic processes of various kinds, and in so doing to describe the possibility spaces associated with these processes. By doing this we explain how it is possible for one process to outperform its rival. Further, in this and similar examples little is gained (...)
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  6. O. B. Lupanov (ed.) (2005). Stochastic Algorithms: Foundations and Applications: Third International Symposium, Saga 2005, Moscow, Russia, October 20-22, 2005: Proceedings. [REVIEW] Springer.score: 90.0
    This book constitutes the refereed proceedings of the Third International Symposium on Stochastic Algorithms: Foundations and Applications, SAGA 2005, held in Moscow, Russia in October 2005. The 14 revised full papers presented together with 5 invited papers were carefully reviewed and selected for inclusion in the book. The contributed papers included in this volume cover both theoretical as well as applied aspects of stochastic computations whith a special focus on new algorithmic ideas involving stochastic decisions and the design and (...)
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  7. Donald Ervin Knuth (2010). Selected Papers on Design of Algorithms. Center for the Study of Language and Information.score: 90.0
  8. William J. Rapaport (2005). Philosophy of Computer Science. Teaching Philosophy 28 (4):319-341.score: 88.0
    There are many branches of philosophy called “the philosophy of X,” where X = disciplines ranging from history to physics. The philosophy of artificial intelligence has a long history, and there are many courses and texts with that title. Surprisingly, the philosophy of computer science is not nearly as well-developed. This article proposes topics that might constitute the philosophy of computer science and describes a course covering those topics, along with suggested readings and assignments.
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  9. Carol E. Cleland (2001). Recipes, Algorithms, and Programs. Minds and Machines 11 (2):219-237.score: 78.0
    In the technical literature of computer science, the concept of an effective procedure is closely associated with the notion of an instruction that precisely specifies an action. Turing machine instructions are held up as providing paragons of instructions that "precisely describe" or "well define" the actions they prescribe. Numerical algorithms and computer programs are judged effective just insofar as they are thought to be translatable into Turing machine programs. Nontechnical procedures (e.g., recipes, methods) are summarily dismissed as (...)
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  10. Richard Heersmink, Jeroen van den Hoven, Nees Jan van Eck & Jan van den Berg (2011). Bibliometric Mapping of Computer and Information Ethics. Ethics and Information Technology 13 (3):241-249.score: 72.0
    This paper presents the first bibliometric mapping analysis of the field of computer and information ethics (C&IE). It provides a map of the relations between 400 key terms in the field. This term map can be used to get an overview of concepts and topics in the field and to identify relations between information and communication technology concepts on the one hand and ethical concepts on the other hand. To produce the term map, a data set of over thousand (...)
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  11. Nicholas Furl, P. Jonathon Phillips & Alice J. O'Toole (2002). Face Recognition Algorithms and the Other‐Race Effect: Computational Mechanisms for a Developmental Contact Hypothesis. Cognitive Science 26 (6):797-815.score: 72.0
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  12. Timothy R. Colburn (1991). Program Verification, Defeasible Reasoning, and Two Views of Computer Science. Minds and Machines 1 (1):97-116.score: 66.0
    In this paper I attempt to cast the current program verification debate within a more general perspective on the methodologies and goals of computer science. I show, first, how any method involved in demonstrating the correctness of a physically executing computer program, whether by testing or formal verification, involves reasoning that is defeasible in nature. Then, through a delineation of the senses in which programs can be run as tests, I show that the activities of testing and formal (...)
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  13. Rolf Niedermeier (2006). Invitation to Fixed-Parameter Algorithms. Oxford University Press.score: 66.0
    A fixed-parameter is an algorithm that provides an optimal solution to a combinatorial problem. This research-level text is an application-oriented introduction to the growing and highly topical area of the development and analysis of efficient fixed-parameter algorithms for hard problems. The book is divided into three parts: a broad introduction that provides the general philosophy and motivation; followed by coverage of algorithmic methods developed over the years in fixed-parameter algorithmics forming the core of the book; and a discussion of (...)
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  14. Jeff Edmonds (2008). How to Think About Algorithms. Cambridge University Press.score: 66.0
    There are many algorithm texts that provide lots of well-polished code and proofs of correctness. Instead, this book presents insights, notations, and analogies to help the novice describe and think about algorithms like an expert. By looking at both the big picture and easy step-by-step methods for developing algorithms, the author helps students avoid the common pitfalls. He stresses paradigms such as loop invariants and recursion to unify a huge range of algorithms into a few meta-algorithms. (...)
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  15. Fahiem Bacchus & Toby Walsh (eds.) (2005). Theory and Applications of Satisfiability Testing: 8th International Conference, Sat 2005, St Andrews, Uk, June 19-23, 2005: Proceedings. [REVIEW] Springer.score: 66.0
    This book constitutes the refereed proceedings of the 8th International Conference on Theory and Applications of Satisfiability Testing, SAT 2005, held in St Andrews, Scotland in June 2005. The 26 revised full papers presented together with 16 revised short papers presented as posters during the technical programme were carefully selected from 73 submissions. The whole spectrum of research in propositional and quantified Boolean formula satisfiability testing is covered including proof systems, search techniques, probabilistic analysis of algorithms and their properties, (...)
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  16. M. W. Bunder & R. M. Rizkalla (2009). Proof-Finding Algorithms for Classical and Subclassical Propositional Logics. Notre Dame Journal of Formal Logic 50 (3):261-273.score: 66.0
    The formulas-as-types isomorphism tells us that every proof and theorem, in the intuitionistic implicational logic $H_\rightarrow$, corresponds to a lambda term or combinator and its type. The algorithms of Bunder very efficiently find a lambda term inhabitant, if any, of any given type of $H_\rightarrow$ and of many of its subsystems. In most cases the search procedure has a simple bound based roughly on the length of the formula involved. Computer implementations of some of these procedures were done (...)
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  17. Holger H. Hoos & David G. Mitchell (eds.) (2005). Theory and Applications of Satisfiability Testing: 7th International Conference, Sat 2004, Vancouver, Bc, Canada, May 10-13, 2004: Revised Selected Papers. [REVIEW] Springer.score: 66.0
    This book constitutes the refereed proceedings of the 7th International Conference on Theory and Applications of Satisfiability Testing, SAT 2004, held in Vancouver, BC, Canada in May 2004. The 24 revised full papers presented together with 2 invited papers were carefully selected from 72 submissions. In addition there are 2 reports on the 2004 SAT Solver Competition and the 2004 QBF Solver Evaluation. The whole spectrum of research in propositional and quantified Boolean formula satisfiability testing is covered; bringing together the (...)
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  18. Ofer Strichman & Stefan Szeider (eds.) (2010). Theory and Applications of Satisfiability Testing-- Sat 2010: 13th International Conference, Sat 2010 Edinburgh, Uk, July 2010: Proceedings. [REVIEW] Springer.score: 66.0
    The LNCS series reports state-of-the-art results in computer science research, development, and education, at a high level and in both printed and electronic form.
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  19. Kiyoko F. Aoki-Kinoshita, Minoru Kanehisa, Ming-Yang Kao, Xiang-Yang Li & Weizhao Wang (2006). Session 2A-Approximation Algorithms-A 6-Approximation Algorithm for Computing Smallest Common AoN-Supertree with Application to the Reconstruction of Glycan Trees. [REVIEW] In O. Stock & M. Schaerf (eds.), Lecture Notes in Computer Science. Springer-Verlag. 100-110.score: 66.0
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  20. Boyana Norris (2006). Minisymposia-VIII Advanced Algorithms and Software Components for Scientific Computing-Software Architecture Issues in Scientific Component Development. In O. Stock & M. Schaerf (eds.), Lecture Notes in Computer Science. Springer-Verlag. 3732--629.score: 66.0
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  21. Jianfeng Shen, Chun Jin & Peng Gao (2006). Evolutionary Computation: Theory and Algorithms-A Nested Genetic Algorithm for Optimal Container Pick-Up Operation Scheduling on Container Yards. In O. Stock & M. Schaerf (eds.), Lecture Notes in Computer Science. Springer-Verlag. 4221--666.score: 66.0
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  22. Christian Weihrauch, Ivan Dimov, Simon Branford & Vassil Alexandrov (2006). Parallel Monte Carlo Algorithms for Diverse Applications in a Distributed Setting-Comparison of the Computational Cost of a Monte Carlo and Deterministic Algorithm for Computing Bilinear Forms Of. In O. Stock & M. Schaerf (eds.), Lecture Notes in Computer Science. Springer-Verlag. 640-647.score: 66.0
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  23. David A. Nelson (1992). Deductive Program Verification (a Practitioner's Commentary). Minds and Machines 2 (3):283-307.score: 60.0
    A proof of ‘correctness’ for a mathematical algorithm cannot be relevant to executions of a program based on that algorithm because both the algorithm and the proof are based on assumptions that do not hold for computations carried out by real-world computers. Thus, proving the ‘correctness’ of an algorithm cannot establish the trustworthiness of programs based on that algorithm. Despite the (deceptive) sameness of the notations used to represent them, the transformation of an algorithm into an executable program is a (...)
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  24. Karem A. Sakallah & Laurent Simon (eds.) (2011). Theory and Application of Satisfiability Testing - Sat 2011: 14th International Conference, Sat 2011, Ann Arbor, Mi, Usa, June 19-22, 2011: Proceedings. [REVIEW] Springer.score: 60.0
    This book constitutes the refereed proceedings of the 14th International Conference on Theory and Applications of Satisfiability Testing, SAT 2011, held in Ann Arbor, MI, USA in June 2011.The 25 revised full papers presented together with ...
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  25. F. B. Cannonito (1970). Review: A. Wlodzimierz Mostowski, On the Decidability of Some Problems in Special Classes of Groups; A. Wlodzimierz Mostowski, Computational Algorithms for Deciding Some Problems for Nilpotent Groups. [REVIEW] Journal of Symbolic Logic 35 (3):476-477.score: 60.0
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  26. John Franco, Endre Boros & P. L. Hammer (eds.) (1999). The Satisfiability Problem. Elsevier.score: 60.0
  27. M. Ben-Ari (1993/2003). Mathematical Logic for Computer Science. Prentice Hall.score: 54.0
    Mathematical Logic for Computer Science is a mathematics textbook with theorems and proofs, but the choice of topics has been guided by the needs of computer science students. The method of semantic tableaux provides an elegant way to teach logic that is both theoretically sound and yet sufficiently elementary for undergraduates. To provide a balanced treatment of logic, tableaux are related to deductive proof systems.The logical systems presented are:- Propositional calculus (including binary decision diagrams);- Predicate calculus;- Resolution;- Hoare (...)
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  28. J. C. Kunz, E. H. Shortliffe, B. G. Buchanan & E. A. Feigenbaum (1984). Computer-Assisted Decision Making in Medicine. Journal of Medicine and Philosophy 9 (2):135-160.score: 54.0
    This article reviews the strengths and limitations of five major paradigms of medical computer-assisted decision making (CADM): (1) clinical algorithms, (2) statistical analysis of collections of patient data, (3) mathematical models of physical processes, (4) decision analysis, and (5) symbolic reasoning or artificial intelligence (Al). No one technique is best for all applications, and there is recent promising work which combines two or more established techniques. We emphasize both the inherent power of symbolic reasoning and the promise of (...)
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  29. Peter Wegner (1999). Towards Empirical Computer Science. The Monist 82 (1):58-108.score: 54.0
    Part I presents a model of interactive computation and a metric for expressiveness, Part II relates interactive models of computation to physics, and Part III considers empirical models from a philosophical perspective. Interaction machines, which extend Turing Machines to interaction, are shown in Part I to be more expressive than Turing Machines by a direct proof, by adapting Gödel's incompleteness result, and by observability metrics. Observation equivalence provides a tool for measuring expressiveness according to which interactive systems are more expressive (...)
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  30. Robert L. Constable, The Triumph of Types: Principia Mathematica's Impact on Computer Science.score: 54.0
    Types now play an essential role in computer science; their ascent originates from Principia Mathematica. Type checking and type inference algorithms are used to prevent semantic errors in programs, and type theories are the native language of several major interactive theorem provers. Some of these trace key features back to Principia.
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  31. A. Feigenbaum Edward (1984). Computer-Assisted Decision Making in Medicine. Journal of Medicine and Philosophy 9 (2).score: 54.0
    This article reviews the strengths and limitations of five major paradigms of medical computer-assisted decision making (CADM): (1) clinical algorithms, (2) statistical analysis of collections of patient data, (3) mathematical models of physical processes, (4) decision analysis, and (5) symbolic reasoning or artificial intelligence (Al). No one technique is best for all applications, and there is recent promising work which combines two or more established techniques. We emphasize both the inherent power of symbolic reasoning and the promise of (...)
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  32. G. J. Chaitin, How to Run Algorithmic Information Theory on a Computer.score: 52.0
    Hi everybody! It's a great pleasure for me to be back here at the new, improved Santa Fe Institute in this spectacular location. I guess this is my fourth visit and it's always very stimulating, so I'm always very happy to visit you guys. I'd like to tell you what I've been up to lately. First of all, let me say what algorithmic information theory is good for, before telling you about the new version of it I've got.
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  33. Jakub Szymanik (2009). Quantifiers in TIME and SPACE. Computational Complexity of Generalized Quantifiers in Natural Language. Dissertation, University of Amsterdamscore: 50.0
    In the dissertation we study the complexity of generalized quantifiers in natural language. Our perspective is interdisciplinary: we combine philosophical insights with theoretical computer science, experimental cognitive science and linguistic theories. -/- In Chapter 1 we argue for identifying a part of meaning, the so-called referential meaning (model-checking), with algorithms. Moreover, we discuss the influence of computational complexity theory on cognitive tasks. We give some arguments to treat as cognitively tractable only those problems which can be computed in (...)
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  34. James H. Fetzer (1994). Mental Algorithms: Are Minds Computational Systems? Pragmatics and Cognition 21 (1):1-29.score: 50.0
  35. Jiri Becvar (1967). Review: J. Hartmanis, R. E. Stearns, On the Computational Complexity of Algorithms. [REVIEW] Journal of Symbolic Logic 32 (1):120-121.score: 50.0
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  36. Alonzo Church (1963). Review: B. A. Trakhtenbrot, Algorithms and Automatic Computing Machines. [REVIEW] Journal of Symbolic Logic 28 (1):104-105.score: 50.0
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  37. Robert Wilensky (1990). Computability, Consciousness, and Algorithms. Behavioral and Brain Sciences 13 (4):690-691.score: 50.0
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  38. Gary Lupyan (2013). The Difficulties of Executing Simple Algorithms: Why Brains Make Mistakes Computers Don't. Cognition 129 (3):615-636.score: 50.0
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  39. Jiri Becvar (1970). Review: B. A. Trahtenbrot, Complexity of Algorithms and Computations (Special Course for Students of the Novosibirsk Government University). [REVIEW] Journal of Symbolic Logic 35 (2):337-339.score: 50.0
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  40. Kenneth Mark Colby (1980). From Computational Metaphor to Consensual Algorithms. Behavioral and Brain Sciences 3 (1):134.score: 50.0
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  41. S. Luan, L. Magnani & G. Dai (2006). Algorithms for Computing Minimal Conflicts. Logic Journal of the Igpl 14:391--406.score: 50.0
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  42. Andre Scedrov (1986). On the Impossibility of Explicit Upper Bounds on Lengths of Some Provably Finite Algorithms in Computable Analysis. Annals of Pure and Applied Logic 32:291-297.score: 50.0
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  43. Jeffrey Barrett (2004). Computer Implication and the Curry Paradox. Journal of Philosophical Logic 33 (6):631 - 637.score: 48.0
    There are theoretical limitations to what can be implemented by a computer program. In this paper we are concerned with a limitation on the strength of computer implemented deduction. We use a version of the Curry paradox to arrive at this limitation.
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  44. Wayne Aitken & Jeffrey A. Barrett (2004). Computer Implication and the Curry Paradox. Journal of Philosophical Logic 33 (6):631-637.score: 48.0
    There are theoretical limitations to what can be implemented by a computer program. In this paper we are concerned with a limitation on the strength of computer implemented deduction. We use a version of the Curry paradox to arrive at this limitation.
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  45. Lev Manovich (2000). Database as a Genre of New Media. AI and Society 14 (2):176-183.score: 48.0
    After the novel, and subsequently cinema privileged narrative as the key form of cultural expression of the modern age, the computer age introduces its correlate — database. Why does new media favour database form over others? Can we explain ist popularity by analysing the specificity of the digital medium and of computer programming? What is the relationship between database and another form, which has traditionally dominated human culture — narrative? In addressing these questions, I discuss the connection between (...)
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  46. Patrick Saint-Dizier & Evelyne Viegas (eds.) (1995). Computational Lexical Semantics. Cambridge University Press.score: 44.0
    Lexical semantics has become a major research area within computational linguistics, drawing from psycholinguistics, knowledge representation, computer algorithms and architecture. Research programmes whose goal is the definition of large lexicons are asking what the appropriate representation structure is for different facets of lexical information. Among these facets, semantic information is probably the most complex and the least explored.Computational Lexical Semantics is one of the first volumes to provide models for the creation of various kinds of computerised lexicons for (...)
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  47. Han Geurdes, The Construction of Transfinite Equivalence Algorithms.score: 42.0
    Context: Consistency of mathematical constructions in numerical analysis and the application of computerized proofs in the light of the occurrence of numerical chaos in simple systems. Purpose: To show that a computer in general and a numerical analysis in particular can add its own peculiarities to the subject under study. Hence the need of thorough theoretical studies on chaos in numerical simulation. Hence, a questioning of what e.g. a numerical disproof of a theorem in physics or a prediction in (...)
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  48. Vitoantonio Bevilacqua, Giuseppe Mastronardi & Filippo Menolascina (2006). Intelligent Computing in Bioinformatics-Genetic Algorithm and Neural Network Based Classification in Microarray Data Analysis with Biological Validity Assessment. In O. Stock & M. Schaerf (eds.), Lecture Notes in Computer Science. Springer-Verlag. 4115--475.score: 42.0
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  49. Joris Van Deun & Ronald Cools (2006). Methods and Software for Computing Mathematical Functions-A Matlab Implementation of an Algorithm for Computing Integrals of Products of Bessel Functions. In O. Stock & M. Schaerf (eds.), Lecture Notes in Computer Science. Springer-Verlag. 284-295.score: 42.0
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  50. T. Lambert, E. Monfroy & F. Saubion (2006). Hybrid Computational Methods and New Algorithmic Approaches to Computational Kernels and Applications-A Generic Framework for Local Search: Application to the Sudoku Problem. In O. Stock & M. Schaerf (eds.), Lecture Notes in Computer Science. Springer-Verlag. 3991--641.score: 42.0
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