3,029 research outputs found
Hyperauthorship in Mikhail Bakhtin: The Primary Author and Conceptual Personae
No full textThis article explores the phemenon of hyperauthorship in intellectual writing: a primary author (hyperauthor) creates a number of secondary authors (hypoauthors), and develops possible conceptual systems on their behalf. The case under consideration is Mikhail Bakhtin and his complex relationship with his friends Pavel Medvedev and Valentin Voloshinov, members of the so called "Bakhtin's circle" (in the 1920s) who are credited with authorship of several books which may have been actually written by Bakhtin himself. Still unclear from biographical and historical perspectives, this problem of authentic attribution of Medvedev's and Voloshinov's texts can be clarified in the theoretical framework of "hyperauthorship" and "possibilistic thinking." This article applies Bakhtin's own theory of the "primary author immersed in silence," as well as Deleuze and Guattari's notion of "conceptual personae," to explain this case of "shared," or "transferred" authorship. The figures of Voloshinov and Medvedev, though historically real, may be viewed as Bakhtin's projections of "ideal," or "utopian" Marxism in linguistics and literary theory
What are the implications of Curriculum Learning strategy on IRL methods?: Investigating Inverse Reinforcement Learning from Human Behavior
No full textInverse Reinforcement Learning (IRL) is a subfield of Reinforcement Learning (RL) that focuses on recovering the reward function using expert demonstrations. In the field of IRL, Adversarial IRL (AIRL) is a promising algorithm that is postulated to recover non-linear rewards in environments with unknown dynamics. This study investigates the potential benefits of applying the Curriculum Learning (CL) strategy to the AIRL algorithm. For our experiments, we use a randomized partially observable Markov decision process in the form of a grid-world-like environment. Using only expert demonstrations obtained with an RL algorithm under the true reward function, we train AIRL in a variety of configurations and identify an effective curriculum. Our results show, that a well-constructed curriculum can enhance the performance of AIRL twofold in both key aspects: the speed of convergence and the efficiency of using expert demonstrations. We thus conclude that CL can be a useful addition to an AIRL-based solution. Full code is available online in the supplementary material https://github.com/mikhail-vlasenko/curriculum-learning-IRL.CSE3000 Research ProjectComputer Science and Engineerin
On the Depth of Decision Trees with Hypotheses
No full textIn this paper, based on the results of rough set theory, test theory, and exact learning, we investigate decision trees over infinite sets of binary attributes represented as infinite binary information systems. We define the notion of a problem over an information system and study three functions of the Shannon type, which characterize the dependence in the worst case of the minimum depth of a decision tree solving a problem on the number of attributes in the problem description. The considered three functions correspond to (i) decision trees using attributes, (ii) decision trees using hypotheses (an analog of equivalence queries from exact learning), and (iii) decision trees using both attributes and hypotheses. The first function has two possible types of behavior: logarithmic and linear (this result follows from more general results published by the author earlier). The second and the third functions have three possible types of behavior: constant, logarithmic, and linear (these results were published by the author earlier without proofs that are given in the present paper). Based on the obtained results, we divided the set of all infinite binary information systems into four complexity classes. In each class, the type of behavior for each of the considered three functions does not change
The importance of marketing in the music industry
No full textAuthor: Ekimov Mikhail
Title of the Publication: The importance of marketing in the music industry
Degree Title: Bachelor of International Business
Keywords: Marketing, music industry, metal music, Behemoth
This thesis is a study, analysis, and development of marketing campaigns for aspiring musicians
The thesis will begin with a theory that includes the basic concepts, features, and concepts of marketing in the music industry. Next, the stages of the marketing campaigns of the successful band Behemoth will be reviewed and analyzed. Based on this analysis, it will be possible to under-stand exactly what actions made the band Behemoth successful. Next, a marketing strategy will be created for a budding and not very popular band, The Nomad. For this purpose, the musician of this band will be interviewed, on the basis of which the main marketing problems of the band and the direction of new strategies will be revealed. At the end of the work the main marketing cam-paigns for the development of the marketing strategy of the band at this stage will be made and their effectiveness will be evaluated.
The main goal: to develop marketing strategies for aspiring music groups in the music industry.
The main tasks: Learn the concepts, principles, and functions of marketing in the music industry and how to use them to create own marketing strategies
Muriel Spark as auto-biographer in <i>Curriculum</i> <i>Vitae</i>
No full textExamining Muriel Spark's main aims as an auto-biographer in her work Curriculum Vitae brings important resources in the exploration of the genre of autobiographical writing. This with the theoretical engagement, allows consideration of the critical issues surrounding the roles of author and reader in the construction of the literary self. Spark demands the reader participate in the constructon of textual meaning; overturning the conventions of autobiography, satirising its claims to omniscience and highlighting the impossibility of an authentic voice with regard to the self
Decision trees for regular factorial languages
No full textIn this paper, we study arbitrary regular factorial languages over a finite alphabet Σ. For the set of words L(n) of the length n belonging to a regular factorial language L, we investigate the depth of decision trees solving the recognition and the membership problems deterministically and nondeterministically. In the case of recognition problem, for a given word from L(n), we should recognize it using queries each of which, for some i∈{1,…,n}, returns the ith letter of the word. In the case of membership problem, for a given word over the alphabet Σ of the length n, we should recognize if it belongs to the set L(n) using the same queries. For a given problem and type of trees, instead of the minimum depth h(n) of a decision tree of the considered type solving the problem for L(n), we study the smoothed minimum depth H(n)=max{h(m):m≤n}. With the growth of n, the smoothed minimum depth of decision trees solving the problem of recognition deterministically is either bounded from above by a constant, or grows as a logarithm, or linearly. For other cases (decision trees solving the problem of recognition nondeterministically, and decision trees solving the membership problem deterministically and nondeterministically), with the growth of n, the smoothed minimum depth of decision trees is either bounded from above by a constant or grows linearly. As corollaries of the obtained results, we study joint behavior of smoothed minimum depths of decision trees for the considered four cases and describe five complexity classes of regular factorial languages. We also investigate the class of regular factorial languages over the alphabet {0,1} each of which is given by one forbidden word.Research reported in this publication was supported by King Abdullah University of Science and Technology (KAUST), Saudi Arabia . The author is grateful to the anonymous reviewers for useful remarks and suggestions
On the depth of decision trees over infinite 1-homogeneous binary information systems
No full textIn this paper, we study decision trees, which solve problems defined over a specific subclass of infinite information systems, namely: 1-homogeneous binary information systems. It is proved that the minimum depth of a decision tree (defined as a function on the number of attributes in a problem’s description) grows – in the worst case – logarithmically or linearly for each information system in this class. We consider a number of examples of infinite 1-homogeneous binary information systems, including one closely related to the decision trees constructed by the CART algorithm.Research reported in this publication was supported by King Abdullah University of Science and Technology (KAUST). The author is thankful to Dr. Michal Mankowski for the helpful comments. The author gratefully acknowledges the useful suggestions of the anonymous reviewers
To Act and Learn: A Bakhtinian Exploration of Action Learning
No full textThis paper considers the work of the Russian social philosopher and cultural theorist, Mikhail Mikhailovich Bakhtin as a source of understanding for those involved in action learning. Drawing upon data gathered over two years during the evaluation of 20 action learning sets in the north of England, we will seek to work with the ideas of Bakhtin to consider their value for those involved in action learning. We consider key Bakhtin features such as Making Meaning, Participative Thinking, Theoreticism and Presence, Others and Outsideness, Voices and Carnival to highlight how Bakhtin's can enhance our understanding of the nature of action and learning
Mikhail N. Tsurikov (8.02.1963 – 4.02.2017)
No full textOn 4 February 2017 Mikhail N. Tsurikov passed away suddenly and prematurely. He was a PhD candidate, a talented scientist, senior researcher, head of the Laboratory of Entomology, head of the fund collections of invertebrates in the State Reserve «Galichya Gora». Mikhail N. Tsurikov was the author of 372 scientific publications, 97 popular scientific articles, two authorship certificates, four invention patents in the following scientific fields: studies of fauna and Coleoptera ecology as well as development of methods for studies of invertebrates
Mikhail Gorbachev's "new thinking": implications for western security
No full textThis thesis examines some of the most important policies encompassed within
Mikhail Gorbachev's "new thinking." The author explores the economic incentives and
shifting Soviet view of international relations which led Gorbachev to introduce his
groundbreaking reforms. Primary emphasis is given to an in-depth analysis of the
"defensive doctrine" and how the issues surrounding that doctrine will impact upon the
future U.S.-Soviet security relationship. Special topics include: increasing evidence of
changes under way in the structure of Soviet forces stationed in Eastern Europe; possible
future Soviet force deployments inside the USSR, including the construction of "fortified
regions," and the evolving U.S.-Soviet relationship in the most important theater of
relations between the two countries—Europe. It is the author's contention that the central
driving force behind all of Gorbachev's reforms was, and remains, a resuscitation of the
Soviet economy. The author concludes that ultimate Soviet objectives under "new
thinking" will remain uncertain, and that the only prudent U.S. policy is to bargain in a vigorous but businesslike manner with Gorbachev to further reduce the Soviet threat, while
retaining defenses sufficient to react to possible future Kremlin backtracking.Approved for public release; distribution is unlimited.Captain, United States Air Forcehttp://archive.org/details/mikhailgorbachev109452835
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