Relevant bibliographies by topics / Randomization

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Randomization'

Author: Grafiati
Published: 4 June 2021
Last updated: 10 March 2023

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Journal articles on the topic "Randomization"

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Hong, Jin Ho, and Jae Chul Yoo. "Randomization, What is the Proper Method?" Journal of the Korean Shoulder and Elbow Society 16, no. 1 (June 30, 2013): 58–62. http://dx.doi.org/10.5397/cise.2013.16.1.58.

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Barnbaum, Deborah R. "Randomization Among: The Other Randomization." Ethics & Human Research 41, no. 5 (September 2019): 35–40. http://dx.doi.org/10.1002/eahr.500031.

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Peto, Richard, and Rory Collins. "Randomization." Nature 372, no. 6507 (December 1994): 588. http://dx.doi.org/10.1038/372588d0.

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Manly, Bryan F. J. "Randomization." Wiley Interdisciplinary Reviews: Computational Statistics 2, no. 3 (April 22, 2010): 383–86. http://dx.doi.org/10.1002/wics.91.

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Zhang, Yanqiong, William F. Rosenberger, and Robert T. Smythe. "Sequential Monitoring of Randomization Tests: Stratified Randomization." Biometrics 63, no. 3 (January 23, 2007): 865–72. http://dx.doi.org/10.1111/j.1541-0420.2006.00735.x.

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Berger, Vance W., Klejda Bejleri, and Rebecca Agnor. "Comparing MTI randomization procedures to blocked randomization." Statistics in Medicine 35, no. 5 (September 3, 2015): 685–94. http://dx.doi.org/10.1002/sim.6637.

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ANDREWS, URI, and H. JEROME KEISLER. "SEPARABLE MODELS OF RANDOMIZATIONS." Journal of Symbolic Logic 80, no. 4 (December 2015): 1149–81. http://dx.doi.org/10.1017/jsl.2015.33.

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AbstractEvery complete first order theory has a corresponding complete theory in continuous logic, called the randomization theory. It has two sorts, a sort for random elements of models of the first order theory, and a sort for events. In this paper we establish connections between properties of countable models of a first order theory and corresponding properties of separable models of the randomization theory. We show that the randomization theory has a prime model if and only if the first order theory has a prime model. And the randomization theory has the same number of separable homogeneous models as the first order theory has countable homogeneous models. We also show that when T has at most countably many countable models, each separable model of TR is uniquely characterized by a probability density function on the set of isomorphism types of countable models of T. This yields an analogue for randomizations of the results of Baldwin and Lachlan on countable models of ω1-categorical first order theories.
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Bailey, R. A., and C. J. Brien. "Randomization-based models for multitiered experiments: I. A chain of randomizations." Annals of Statistics 44, no. 3 (June 2016): 1131–64. http://dx.doi.org/10.1214/15-aos1400.

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Mitchell-Olds, Thomas. "Randomization Methods." Ecology 73, no. 6 (December 1992): 2338–39. http://dx.doi.org/10.2307/1941484.

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Habibzadeh, Farrokh, and Parham Habibzadeh. "Shuffle randomization." Croatian Medical Journal 56, no. 4 (August 2015): 383–84. http://dx.doi.org/10.3325/cmj.2015.56.383.

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Dissertations / Theses on the topic "Randomization"

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Wu, Huayue. "Randomization and Restart Strategies." Thesis, University of Waterloo, 2006. http://hdl.handle.net/10012/2923.

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The runtime for solving constraint satisfaction problems (CSP) and propositional satisfiability problems (SAT) using systematic backtracking search has been shown to exhibit great variability. Randomization and restarts is an effective technique for reducing such variability to achieve better expected performance. Several restart strategies have been proposed and studied in previous work and show differing degrees of empirical effectiveness.

The first topic in this thesis is the extension of analytical results on restart strategies through the introduction of physically based assumptions. In particular, we study the performance of two of the restart strategies on Pareto runtime distributions. We show that the geometric strategy provably removes heavy tail. We also examine several factors that arise during implementation and their effects on existing restart strategies.

The second topic concerns the development of a new hybrid restart strategy in a realistic problem setting. Our work adapts the existing general approach on dynamic strategy but implements more sophisticated machine learning techniques. The resulting hybrid strategy shows superior performance compared to existing static strategies and an improved robustness.
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Palmer, Thomas M. "Extensions to Mendelian randomization." Thesis, University of Leicester, 2009. http://hdl.handle.net/2381/7617.

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The Mendelian randomization approach is concerned with the causal pathway between a gene, an intermediate phenotype and a disease. The aim of the approach is to estimate the causal association between the phenotype and the disease when confounding or reverse causation may affect the direct estimate of this association. The approach represents the use of genes as instrumental variables in epidemiological research and is justified through Mendel's second law. Instrumental variable analysis was developed in econometrics as an alternative to regression analyses affected by confounding and reverse causation. Methods such as two-stage least squares are appropriate for instrumental variable analyses where the phenotype and disease are continuous. However, case-control and cohort studies typically report binary outcomes and instrumental variable methods for these studies are less well developed. For a binary outcome study three estimators of the phenotype-disease log odds ratio are compared. An adjusted instrumental variable estimator is shown to have the least bias compared with the other two estimators. However, significance tests of the adjusted estimator are shown to have an inflated type I error rate, so the standard estimator, which had the correct type I error rate, could be used for testing. A single study may not have adequate statistical power to detect a causal association in a Mendelian randomization analysis. Meta-analysis models that extend existing approaches are investigated. The ratio of coefficients approach is applied within the meta-analysis models and a Taylor series approximation is used to investigate its finite sample bias. The increasing awareness of the Mendelian randomization approach has made researchers aware of the need for instrumental variable methods appropriate for epidemiological study designs. The work in this thesis viewed in the context of the research into instrumental variable analysis in other areas of biostatistics such as non-compliance in clinical trials and other subject areas such as econometrics and causal inference contributes to the development of methods for Mendelian randomization analyses.
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Batidzirai, Jesca Mercy. "Randomization in a two armed clinical trial: an overview of different randomization techniques." Thesis, University of Fort Hare, 2011. http://hdl.handle.net/10353/395.

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Randomization is the key element of any sensible clinical trial. It is the only way we can be sure that the patients have been allocated into the treatment groups without bias and that the treatment groups are almost similar before the start of the trial. The randomization schemes used to allocate patients into the treatment groups play a role in achieving this goal. This study uses SAS simulations to do categorical data analysis and comparison of differences between two main randomization schemes namely unrestricted and restricted randomization in dental studies where there are small samples, i.e. simple randomization and the minimization method respectively. Results show that minimization produces almost equally sized treatment groups, but simple randomization is weak in balancing prognostic factors. Nevertheless, simple randomization can also produce balanced groups even in small samples, by chance. Statistical power is also improved when minimization is used than in simple randomization, but bigger samples might be needed to boost the power.
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LaValley, Jason. "Next Generation RFID Randomization Protocol." Thèse, Université d'Ottawa / University of Ottawa, 2011. http://hdl.handle.net/10393/20471.

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Radio Frequency IDentification (RFID) is a wireless communications technology which allows companies to secure their assets and increase the portability of information. This research was motivated by the increased commercial use of RFID technology. Existing security protocols with high levels of security have high computation requirements, and less intensive protocols can allow a tag to be tracked. The techniques proposed in this thesis result in the increase of ciphertexts available without a significant increase in processing power or storage requirements. The addition of random inputs to the generation of ciphertexts will increase the number of possible results without requiring a more advanced encryption algorithm or an increased number of stored encryption keys. Four methods of altering the plaintext/ciphertext pair (random block, set pattern, random pattern, and indexed placement) are analyzed to determine the effectiveness of each method. The number of ciphertexts generated, generation time, and generation errors were recorded to determine which of the four proposed methods would be the most beneficial in a RFID system. The comparison of these method characteristics determined that the set pattern placement method provided the best solution. The thesis also discusses how RFID transmissions appear to attackers and explains how the random inputs reduce effectiveness of current system attacks. In addition to improving the anonymity of RFID tag transmissions, the concept of authenticating random inputs is also introduced in this thesis. These methods help prevent an adversary from easily associating a tag with its transmissions, thus increasing the security of the RFID system.
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Pobbathi, Venkatesh Paneesh Kumar. "Randomization Based Verification for Microprocessors." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-177438.

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Verification of microprocessors is a vital phase in their development. It takes majority of time and cost in the microprocessor development. Verification can be split into two; coverage and check. In coverage we try to find out if all desired conditions are executed. Where as in check, we try to find out if the behaviour of the DUT is as expected. In this thesis we concentrate more on coverage. The test bench should be able to cover all the cases, hence methodologies have to be used which will not only reduce the total time of the project but also get maximum coverage to increase the bug detection chances. Random simulation helps to quickly attain corner cases that would not have been found by the traditional directed testing. In this thesis functional verification for the microprocessor M6802 was implemented. Few verification approaches were implemented to find out their feasibility. It was found out that random generation had many advantages over directed testing but both the approaches failed to attain good coverage in reasonable time. To overcome this other implementations were explored such as coverage driven and machine learning. Machine learning showed significant improvement over the other methods for coverage on the filp side it required a lot of setup time. It was found out that the combination of these approaches have to be used to reduce the setup time and get maximum coverage. The method to be selected depends on the complexity of the processor and the functional coverpoint.
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Loukas, Vasileios. "Efficient Cache Randomization for Security." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-417725.

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The effectiveness of cache hierarchies, undeniably, is of crucial importance, since they essentially constitute the solution to the disparity between fast processors and high memory latency. Nevertheless, security developments spanning for more than the last decade, critically expose cache hierarchies' vulnerabilities, thus creating a need for counter-measures to take place. Through conflict-based attacks, the access pattern of a co-running application might be inferred, which in turn can be used to leak sensitive information from the application, such as encryption keys. Consequently, different ways of securing cache memories with respect to conflict- based attacks have emerged, ideally incurring neither large storage overhead nor requiring any Operating System support, yet providing both high performance and strong security. Prior work in the field has shown that a static encryption scheme is practically deemed insufficient, thus dynamic remapping policies have been introduced, so that the eviction sets form periodically, making it much harder for an adversary to recognize them. In this thesis project, a randomization technique that leverages the indexing function of a 3-level cache hierarchy (RASCAL) as well as a smooth dynamic remapping policy that further curates the performance gap introduced have been designed and implemented. The performance overhead incurred by our intervention on a typical cache hierarchy mechanism is identified, compared and contrasted to another two different remapping policies implemented, eventually exhibiting that it is feasible for a cache to be randomized and dynamically remapped at a sensible security-wise interval with a performance decrease of less than 1% in terms of miss ratio.
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Berry, Eric Dean. "Randomization testing of machine induced rules." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1995. http://handle.dtic.mil/100.2/ADA304271.

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Thesis (M.S. in Information Technology Management) Naval Postgraduate School, September 1995.
"September 1995." Thesis advisor(s): B. Ramesh, William J. Haga. Includes bibliographical references. Also available online.
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Vishnoi, Nisheeth Kumar. "Theoretical Aspects of Randomization in Computation." Diss., Georgia Institute of Technology, 2004. http://hdl.handle.net/1853/6424.

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Randomness has proved to be a powerful tool in all of computation. It is pervasive in areas such as networking, machine learning, computer graphics, optimization, computational number theory and is "necessary" for cryptography. Though randomized algorithms and protocols assume access to "truly" random bits, in practice, they rely on the output of "imperfect" sources of randomness such as pseudo-random number generators or physical sources. Hence, from a theoretical standpoint, it becomes important to view randomness as a resource and to study the following fundamental questions pertaining to it: Extraction: How do we generate "high quality" random bits from "imperfect" sources? Randomization: How do we use randomness to obtain efficient algorithms? Derandomization: How (and when) can we "remove" our dependence on random bits? In this thesis, we consider important problems in these three prominent and diverse areas pertaining to randomness. In randomness extraction, we present extractors for "oblivious bit fixing sources". In (a non-traditional use of) randomization, we have obtained results in machine learning (learning juntas) and proved hardness of lattice problems. While in derandomization, we present a deterministic algorithm for a fundamental problem called "identity testing". In this thesis we also initiate a complexity theoretic study of Hilbert's 17th problem. Here identity testing is used in an interesting manner. A common theme in this work has been the use of tools from areas such as number theory in a variety of ways, and often the techniques themselves are quite interesting.
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Johnston, Robert S. "Modeling the effects of restricted randomization." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape15/PQDD_0003/NQ31993.pdf.

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Letsou, Christina. "Preferences for Randomization in Social Choice:." Thesis, Boston College, 2020. http://hdl.handle.net/2345/bc-ir:108719.

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Thesis advisor: Uzi Segal
This dissertation consists of three chapters analyzing preferences for randomization in social choice problems. The first two chapters are related and in the fields of distributive justice and social choice. They concern allocation of an indivisible good in social choice problems where efficiency is at odds with equality. The last chapter addresses a social choice problem from an individual's perspective using decision theoretical analysis. In this dissertation I demonstrate why randomization may be an attractive policy in social choice problems and demonstrate how individuals may have preferences over the precise method of randomization. The first chapter is titled "Live and Let Die." This paper discusses how to allocate an indivisible good by social lottery when agents have asymmetric claims. Intuition suggests that there may exist agents who should receive zero probability in the optimal social lottery. In such a case, I say that these agents have weak claims to the good. This paper uses a running example of allocating an indivisible medical treatment to individuals with different survival rates and reactions to the treatment in order to provide conditions for consistency of weak claims. As such, I develop two related assumptions on a social planner's preferences over lotteries. The first -- survival rate scaling -- states that if an individual has a weak claim, then his claim is also weak when survival rates increase proportionally. The second -- independence of weak claims -- states that if an individual has a weak claim, then his removal does not affect others' probabilities of receiving the treatment. These assumptions imply that a compatible social welfare function must exhibit constant elasticity of substitution, which results in potentially-degenerate weighted lotteries. The second chapter is titled "Why is Six Afraid of Seven? Bringing the "Numbers" to Economics." This chapter discusses the numbers problem: the question of if the numbers of people involved should be used to determine whether to help certain people or to help certain other people. I discuss the main solutions that have been proposed: flipping a coin, saving the greater number, and proportionally weighted lotteries. Using the economic tools of social choice, I then show how the model of the previous chapter, "Live and Let Die," can be extended to address numbers problems and compare the implications of prominent social welfare functions for numbers problems. I argue that potentially-degenerate weighted lotteries can assuage the main concerns discussed in the literature and I show that both the Nash product social welfare function as well as constant elasticity of substitution (CES) social welfare functions are compatible with this solution. Finally, I discuss a related problem known as "probability cases," in which individuals differ in survival chances rather than numbers of individuals at risk. When the model is extended to allow for both asymmetries in survival chances and numbers of individuals in groups, CES results in potentially-degenerate weighted lotteries whereas Nash product does not. The third chapter is titled "All Probabilities are Equal, but Some Probabilities are More Equal than Others," which is joint work with Professor Uzi Segal of the Economics Department at Boston College and Professor Shlomo Naeh of the Departments of Talmud and Jewish Thought at The Hebrew University of Jerusalem. In this chapter we compare preferences for different procedures of selecting people randomly. A common procedure for selecting people is to have them draw balls from an urn in turn. Modern and ancient stories (for example, by Graham Greene and the Talmud) suggest that such a lottery may not be viewed by the individuals as "fair.'' In this paper, we compare this procedure with several alternatives. These procedures give all individuals equal chance of being selected, but have different structures. We analyze these procedures as multi-stage lotteries. In line with previous literature, our analysis is based on the observation that multi-stage lotteries are not considered indifferent to their probabilistic one-stage representations. As such, we use a non-expected utility model to understand the preferences of risk-averse individuals over these procedures and show that they may be not indifferent between them
Thesis (PhD) — Boston College, 2020
Submitted to: Boston College. Graduate School of Arts and Sciences
Discipline: Economics
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Books on the topic "Randomization"

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Edgington, Eugene S. Randomization tests. 3rd ed. New York: M. Dekker, 1995.

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Randomization tests. 3rd ed. New York: M. Dekker, 1995.

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Patrick, Onghena, ed. Randomization tests. 4th ed. Boca Raton, Fla: Taylor & Francis, 2007.

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Randomization tests. 2nd ed. New York: M. Dekker, 1987.

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Rosenberger, William F., and John M. Lachin. Randomization in Clinical Trials. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2002. http://dx.doi.org/10.1002/0471722103.

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Rosenberger, William F., and John M. Lachin. Randomization in Clinical Trials. Hoboken, NJ, USA: John Wiley & Sons, Inc, 2016. http://dx.doi.org/10.1002/9781118742112.

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F, Boruch Robert, and Wothke Werner 1952-, eds. Randomization and field experimentation. San Francisco: Jossey-Bass, 1985.

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Berger, Vance W., ed. Randomization, Masking, and Allocation Concealment. Boca Raton : Taylor & Francis, a CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the academic division of T&F Informa plc, 2018.: Chapman and Hall/CRC, 2017. http://dx.doi.org/10.1201/9781315305110.

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Caliński, Tadeusz, and Sanpei Kageyama. Block Designs: A Randomization Approach. New York, NY: Springer New York, 2003. http://dx.doi.org/10.1007/978-1-4419-9246-8.

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Caliński, Tadeusz, and Sanpei Kageyama. Block Designs: A Randomization Approach. New York, NY: Springer New York, 2000. http://dx.doi.org/10.1007/978-1-4612-1192-1.

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Book chapters on the topic "Randomization"

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Spear, Chris. "Randomization." In System Verilog for Verification, 161–216. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-76530-3_6.

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Spear, Chris, and Greg Tumbush. "Randomization." In SystemVerilog for Verification, 169–227. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-1-4614-0715-7_6.

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Gooch, Jan W. "Randomization." In Encyclopedic Dictionary of Polymers, 993. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-6247-8_15342.

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Turner, J. Rick. "Randomization." In Encyclopedia of Behavioral Medicine, 1841. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39903-0_1057.

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Molina, Kristine M., Kristine M. Molina, Heather Honoré Goltz, Marc A. Kowalkouski, Stacey L. Hart, David Latini, J. Rick Turner, et al. "Randomization." In Encyclopedia of Behavioral Medicine, 1618–19. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-1005-9_1057.

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Nahler, Gerhard. "randomization." In Dictionary of Pharmaceutical Medicine, 154–55. Vienna: Springer Vienna, 2009. http://dx.doi.org/10.1007/978-3-211-89836-9_1179.

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Berger, James O. "Randomization." In Time Series and Statistics, 208–10. London: Palgrave Macmillan UK, 1990. http://dx.doi.org/10.1007/978-1-349-20865-4_28.

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Berger, James O. "Randomization." In The New Palgrave Dictionary of Economics, 1–3. London: Palgrave Macmillan UK, 1987. http://dx.doi.org/10.1057/978-1-349-95121-5_1593-1.

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Ferraz, Cristiano. "Randomization." In International Encyclopedia of Statistical Science, 1180–82. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-04898-2_470.

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Komm, Dennis. "Randomization." In Texts in Theoretical Computer Science. An EATCS Series, 31–83. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-42749-2_2.

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Conference papers on the topic "Randomization"

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Carrasco, Juan A., and Angel Calderón. "Regenerative randomization." In the 1995 ACM SIGMETRICS joint international conference. New York, New York, USA: ACM Press, 1995. http://dx.doi.org/10.1145/223587.223613.

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Zhang, Kai, Chuanren Liu, Jie Zhang, Hui Xiong, Eric Xing, and Jieping Ye. "Randomization or Condensation?" In KDD '17: The 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3097983.3098050.

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Nguyen, Thien Duc, Markus Miettinen, and Ahmad-Reza Sadeghi. "Long Live Randomization." In CCS '20: 2020 ACM SIGSAC Conference on Computer and Communications Security. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3411496.3421229.

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Ugander, Johan, Brian Karrer, Lars Backstrom, and Jon Kleinberg. "Graph cluster randomization." In KDD' 13: The 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2013. http://dx.doi.org/10.1145/2487575.2487695.

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Xu, Haizhi, and Steve J. Chapin. "Improving address space randomization with a dynamic offset randomization technique." In the 2006 ACM symposium. New York, New York, USA: ACM Press, 2006. http://dx.doi.org/10.1145/1141277.1141364.

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Sinha, Kanad, Vasileios P. Kemerlis, and Simha Sethumadhavan. "Reviving instruction set randomization." In 2017 IEEE International Symposium on Hardware Oriented Security and Trust (HOST). IEEE, 2017. http://dx.doi.org/10.1109/hst.2017.7951732.

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Koo, Hyungjoon, Yaohui Chen, Long Lu, Vasileios P. Kemerlis, and Michalis Polychronakis. "Compiler-Assisted Code Randomization." In 2018 IEEE Symposium on Security and Privacy (SP). IEEE, 2018. http://dx.doi.org/10.1109/sp.2018.00029.

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Rocha, Anderson, and Siome Goldenstein. "Progressive Randomization for Steganalysis." In 2006 IEEE Workshop on Multimedia Signal Processing. IEEE, 2006. http://dx.doi.org/10.1109/mmsp.2006.285321.

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Melcher, Jordan L., Yao Zheng, Dylan Anthony, Matthew Troglia, Thomas Yang, Alvin Yang, Samson Aggelopoulos, Yanjun Pan, and Ming Li. "iJam with channel randomization." In WiSec '20: 13th ACM Conference on Security and Privacy in Wireless and Mobile Networks. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3395351.3401705.

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Hanhijärvi, Sami, Gemma C. Garriga, and Kai Puolamäki. "Randomization Techniques for Graphs." In Proceedings of the 2009 SIAM International Conference on Data Mining. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2009. http://dx.doi.org/10.1137/1.9781611972795.67.

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Reports on the topic "Randomization"

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Arnott, Richard, and Joseph Stiglitz. Randomization with Asymmetric Information. Cambridge, MA: National Bureau of Economic Research, February 1988. http://dx.doi.org/10.3386/w2507.

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Heckman, James. Randomization as an Instrumental Variable. Cambridge, MA: National Bureau of Economic Research, September 1995. http://dx.doi.org/10.3386/t0184.

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Shaikh, Azeem M., Federico A. Bugni, and Ivan A. Canay. Inference under covariate-adaptive randomization. Institute for Fiscal Studies, August 2015. http://dx.doi.org/10.1920/wp.cem.2015.4515.

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Bugni, Federico A., Ivan A. Canay, and Azeem M. Shaikh. Inference under Covariate-Adaptive Randomization. IFS, May 2016. http://dx.doi.org/10.1920/wp.cem.2016.2116.

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Shaikh, Azeem M., Ivan A. Canay, and Federico A. Bugni. Inference under covariate-adaptive randomization. The IFS, May 2017. http://dx.doi.org/10.1920/wp.cem.2017.2517.

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Heckman, James. Randomization and Social Policy Evaluation Revisited. Cambridge, MA: National Bureau of Economic Research, July 1991. http://dx.doi.org/10.3386/t0107.

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Larsen, M., and F. Gont. Recommendations for Transport-Protocol Port Randomization. RFC Editor, January 2011. http://dx.doi.org/10.17487/rfc6056.

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8

Barrios, Thomas, Rebecca Diamond, Guido Imbens, and Michal Kolesar. Clustering, Spatial Correlations and Randomization Inference. Cambridge, MA: National Bureau of Economic Research, February 2010. http://dx.doi.org/10.3386/w15760.

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Brito, Dagobert, Jonathan Hamilton, Steven Slutsky, and Joseph Stiglitz. Randomization in Optimal Income Tax Schedules. Cambridge, MA: National Bureau of Economic Research, March 1990. http://dx.doi.org/10.3386/w3289.

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10

Heckman, James. Randomization and Social Policy Evaluation Revisited. The IFS, February 2020. http://dx.doi.org/10.1920/wp.cem.2020.720.

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