797 resultados para Statistical Learning Theory.


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A theory is presented to explain the statistical properties of the growth of dye-laser radiation. Results are in agreement with recent experimental findings. The different roles of pump-noise intensity and correlation time are elucidated.

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This research explored the events that engaged graduate students in transformative learning within a graduate program in education. This context was chosen because one objective of a graduate program is to facilitate critical thinking and transformative learning. The question ofhow adult learners perceive and experience learning steered the direction ofthis study. However, the purpose ofthis research was to study critical incidents that led to profound cognitive and affective changes as perceived by the graduate students. Specifically, the questions to be answered were what critical incidents happened to graduate students while in the Master ofEducation program, how were the incidents experienced, and what transformation resulted? The research design evolved over the course of a year and was highly influenced by previous empirical studies and criticisms oftransformative learning theory. The overall design was qualitative and phenomenological. A critical and interpretive approach was made to empirical data collected through a critical incident questionnaire and in-depth interviews. Inductive analysis allowed theory to be built from the data by making comparisons. New questions emerged and attention was given to social context, the passage oftime, and sequence ofevents in order to give meaning and translation ofthe participants' experiences and to build the interpretive narratives. Deductive analysis was also used on the data and a blending ofthe two forms of analysis; this resulted in the development ofa foundational model for transformative learning to be built.The data revealed critical incidents outside ofthe graduate school program that occurred in childhood or adult life prior to graduate school. Since context of individuals' lives had been an important critique of past transformative learning models and studies, this research expanded the original boundaries of this study beyond graduate school to incorporate incidents that occurred outside of graduate school. Critical incidents were categorized into time-related, people-related, and circumstancerelated themes. It was clear that participants were influenced and molded by the stage oftheir life, personal experiences, familial and cultural conditioning, and even historic events. The model developed in this document fiom an overview ofthe fmdings identifies a four-stage process of life difficulty, disintegration, reintegration, and completion that all participants' followed. The blended analysis was revealed from the description ofhow the incidents were experienced by the participants. The final categories were what were the feelings, what was happening, and what was the enviromnent? The resulting transformation was initially only going to consider cognitive and affective changes, however, it was apparent that contextual changes also occurred for all participants, so this category was also included. The model was described with the construction metaphor of a building "foimdation" to illustrate the variety of conditions that are necessary for transformative learning to occur. Since this was an exploratory study, no prior models or processes were used in data analysis, however, it appeared that the model developed from this study incorporated existing models and provided a more encompassing life picture oftransformative learning.

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The purpose of this qualitative research was to study the learning preferences and styles of management lawyers who work in Ontario's legal aid clinics. Data were gathered from two sources and analyzed using the constant comparison method. A preand postconference survey provided the principal data on clinic lawyers' learning preferences. Follow-up interviews were then conducted with 3 purposefully selected survey participants to explore their personal learning styles. Kolb's experiential learning theory provided the theoretical framework for discussing personal learning styles. The findings showed a general consistency among the lawyers to learn by listening to lectures and experts. This preference may suggest a lingering influence from law school training. The lawyers' more informal learning associated with daily practice, however, appeared to be guided by various learning styles. The learning style discussions provided some support for Kolb's model but also confirmed some shortcomings noted by other authors. Educators who design continuing education programs for lawyers may benefit from some insights gained from this exploratory research. This study adds to a limited but growing body of work on the learning preferences and styles of lawyers and suggests new questions for future research.

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Active learning strategies based on several learning theories were incorporated during instruction sessions for second year Biological Sciences students. The instructional strategies described in this paper are based primarily on sociocultural and collaborative learning theory, with the goal being to expand the relatively small body of literature currently available that discusses the application of these learning theories to library instruction. The learning strategies employed successfully involved students in the learning process ensuring that the experiences were appropriate and effective. The researchers found that, as a result of these strategies (e.g. teaching moments based on the emerging needs of students) students’ interest in learning information literacy was increased and students interacted with information given to them as well as with their peers. Collaboration between the Librarians, Co-op Student and Senior Lab Instructor helped to enhance the learning experience for students and also revealed new aspects of the active learning experiences. The primary learning objective, which was to increase the students’ information skills in the Biological Sciences, was realized. The advantages of active learning were realized by both instructors and students. Advantages for students attained during these sessions include having their diverse learning styles addressed; increased interaction with and retention of information; increased responsibility for their own learning; the opportunity to value not only the instructors, but also themselves and their peers as sources of authority and knowledge; improved problem solving abilities; increased interest and opportunities for critical thinking, as a result of the actively exchanging information in a group. The primary advantage enjoyed by the instructors was the opportunity to collaborate with colleagues to reduce the preparation required to create effective library instruction sessions. Opportunities for further research were also discovered, including the degree to which “social loafing” plays a role in collaborative, active learning.

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This thesis attempts to quantify the amount of information needed to learn certain tasks. The tasks chosen vary from learning functions in a Sobolev space using radial basis function networks to learning grammars in the principles and parameters framework of modern linguistic theory. These problems are analyzed from the perspective of computational learning theory and certain unifying perspectives emerge.

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In most classical frameworks for learning from examples, it is assumed that examples are randomly drawn and presented to the learner. In this paper, we consider the possibility of a more active learner who is allowed to choose his/her own examples. Our investigations are carried out in a function approximation setting. In particular, using arguments from optimal recovery (Micchelli and Rivlin, 1976), we develop an adaptive sampling strategy (equivalent to adaptive approximation) for arbitrary approximation schemes. We provide a general formulation of the problem and show how it can be regarded as sequential optimal recovery. We demonstrate the application of this general formulation to two special cases of functions on the real line 1) monotonically increasing functions and 2) functions with bounded derivative. An extensive investigation of the sample complexity of approximating these functions is conducted yielding both theoretical and empirical results on test functions. Our theoretical results (stated insPAC-style), along with the simulations demonstrate the superiority of our active scheme over both passive learning as well as classical optimal recovery. The analysis of active function approximation is conducted in a worst-case setting, in contrast with other Bayesian paradigms obtained from optimal design (Mackay, 1992).

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Real-world learning tasks often involve high-dimensional data sets with complex patterns of missing features. In this paper we review the problem of learning from incomplete data from two statistical perspectives---the likelihood-based and the Bayesian. The goal is two-fold: to place current neural network approaches to missing data within a statistical framework, and to describe a set of algorithms, derived from the likelihood-based framework, that handle clustering, classification, and function approximation from incomplete data in a principled and efficient manner. These algorithms are based on mixture modeling and make two distinct appeals to the Expectation-Maximization (EM) principle (Dempster, Laird, and Rubin 1977)---both for the estimation of mixture components and for coping with the missing data.

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Regularization Networks and Support Vector Machines are techniques for solving certain problems of learning from examples -- in particular the regression problem of approximating a multivariate function from sparse data. We present both formulations in a unified framework, namely in the context of Vapnik's theory of statistical learning which provides a general foundation for the learning problem, combining functional analysis and statistics.

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En este estudio presentamos una experiencia llevada a cabo con estudiantes de la asignatura “Psicología de la Educación” de diferentes centros universitarios. Tomando como marco de referencia las teorías constructivistas del aprendizaje, el objetivo de nuestro trabajo se centra en comprobar la incidencia de la utilización de diferentes estrategias de enseñanza por parte del profesor y de determinadas estrategias de aprendizaje en el proceso de registrar la información por parte de los estudiantes, en la significatividad del aprendizaje. Los resultados obtenidos muestran que en los grupos donde los profesores han utilizado estrategias de enseñanza diferentes a la clase magistral, se ha producido un cambio positivo en las respuestas de los estudiantes o se ha mantenido el mismo nivel, mientras que el grupo donde se ha utilizado una metodología magistral, el nivel de respuesta es inferior. Así mismo, hemos podido observar como los grupos de estudiantes que utilizan las estrategias de aprendizaje seleccionadas para tomar apuntes mejoran su nivel de respuestas, lo cual no se produce en el grupo control

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By eliminating the short range negative divergence of the Debye–Hückel pair distribution function, but retaining the exponential charge screening known to operate at large interparticle separation, the thermodynamic properties of one-component plasmas of point ions or charged hard spheres can be well represented even in the strong coupling regime. Predicted electrostatic free energies agree within 5% of simulation data for typical Coulomb interactions up to a factor of 10 times the average kinetic energy. Here, this idea is extended to the general case of a uniform ionic mixture, comprising an arbitrary number of components, embedded in a rigid neutralizing background. The new theory is implemented in two ways: (i) by an unambiguous iterative algorithm that requires numerical methods and breaks the symmetry of cross correlation functions; and (ii) by invoking generalized matrix inverses that maintain symmetry and yield completely analytic solutions, but which are not uniquely determined. The extreme computational simplicity of the theory is attractive when considering applications to complex inhomogeneous fluids of charged particles.

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Purpose – The purpose of this paper is to investigate to what extent one can apply experiential learning theory (ELT) to the public-private partnership (PPP) setting in Russia and to draw insights regarding the learning cycle ' s nature. Additionally, the paper assesses whether the PPP case confirms Kolb ' s ELT. Design/methodology/approach – The case study draws upon primary data which the authors collected by interviewing informants including a PPP operator ' s managers, lawyers from Russian law firms and an expert from the National PPP Centre. The authors accomplished data source triangulation in order to ensure a high degree of research validity. Findings – Experiential learning has resulted in a successful and a relatively fast PPP project launch without the concessionary framework. The lessons learned include the need for effective stakeholder engagement; avoiding being stuck in bureaucracy such as collaboration with Federal Ministries and anti-trust agency; avoiding application for government funding as the approval process is tangled and lengthy; attracting strategic private investors; shaping positive public perception of a PPP project; and making continuous efforts in order to effectively mitigate the public acceptance risk. Originality/value – The paper contributes to ELT by incorporating the impact of social environment in the learning model. Additionally, the paper tests the applicability of ELT to learning in the complex organisational setting, i.e., a PPP.

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Using the functional integral formalism for the statistical generating functional in the statistical (finite temperature) quantum field theory, we prove the equivalence of many-photon Greens functions in the Duffin-Kennner-Petiau and Klein-Gordon-Fock statistical quantum field theories. As an illustration, we calculate the one-loop polarization operators in both theories and demonstrate their coincidence.

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We contrast four distinct versions of the BCS-Bose statistical crossover theory according to the form assumed for the electron-number equation that accompanies the BCS gap equation. The four versions correspond to explicitly accounting for two-hole-(2h) as well as two-electron-(2e) Cooper pairs (CPs), or both in equal proportions, or only either kind. This follows from a recent generalization of the Bose-Einstein condensation (GBEC) statistical theory that includes not boson-boson interactions but rather 2e- and also (without loss of generality) 2h-CPs interacting with unpaired electrons and holes in a single-band model that is easily converted into a two-band model. The GBEC theory is essentially an extension of the Friedberg-Lee 1989 BEC theory of superconductors that excludes 2h-CPs. It can thus recover, when the numbers of 2h- and 2e-CPs in both BE-condensed and non-condensed states are separately equal, the BCS gap equation for all temperatures and couplings as well as the zero-temperature BCS (rigorous-upper-bound) condensation energy for all couplings. But ignoring either 2h- or 2e-CPs it can do neither. In particular, only half the BCS condensation energy is obtained in the two crossover versions ignoring either kind of CPs. We show how critical temperatures T-c from the original BCS-Bose crossover theory in 2D require unphysically large couplings for the Cooper/BCS model interaction to differ significantly from the T(c)s of ordinary BCS theory (where the number equation is substituted by the assumption that the chemical potential equals the Fermi energy). (c) 2007 Published by Elsevier B.V.

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In this thesis we discuss a representation of quantum mechanics and quantum and statistical field theory based on a functional renormalization flow equation for the one-particle-irreducible average effective action, and we employ it to get information on some specific systems.