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Classificação de dados estacionários e não estacionários baseada em grafos; Graph-based classification for stationary and non-stationary data

Bertini Júnior, João Roberto
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Tese de Doutorado Formato: application/pdf
Relevância na Pesquisa
45.82%

Avaliação de instrumento de auxílio à escrita científica em inglês fundamentado na aprendizagem baseada em exemplos e em experiências aplicado em alunos pós-graduandos em Engenharia de Produção; Assessment of tool to aid scientific writing in English grounded on example- and experience-based learning applied to Production Engineering graduate students

Reith, Ralf Landim
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Dissertação de Mestrado Formato: application/pdf
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75.94%

Example Based Learning for View-Based Human Face Detection

Sung, Kah Kay; Poggio, Tomaso
Fonte: MIT - Massachusetts Institute of Technology Publicador: MIT - Massachusetts Institute of Technology
Formato: 21 p.; 2933946 bytes; 846344 bytes; application/postscript; application/pdf
EN_US
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We present an example-based learning approach for locating vertical frontal views of human faces in complex scenes. The technique models the distribution of human face patterns by means of a few view-based "face' and "non-face' prototype clusters. At each image location, the local pattern is matched against the distribution-based model, and a trained classifier determines, based on the local difference measurements, whether or not a human face exists at the current image location. We provide an analysis that helps identify the critical components of our system.

Shakhnarovich, Gregory
Fonte: Massachusetts Institute of Technology Publicador: Massachusetts Institute of Technology
Tipo: Tese de Doutorado Formato: 147 p.
ENG
Relevância na Pesquisa
45.82%
The right measure of similarity between examples is important in many areas of computer science. In particular it is a critical component in example-based learning methods. Similarity is commonly defined in terms of a conventional distance function, but such a definition does not necessarily capture the inherent meaning of similarity, which tends to depend on the underlying task. We develop an algorithmic approach to learning similarity from examples of what objects are deemed similar according to the task-specific notion of similarity at hand, as well as optional negative examples. Our learning algorithm constructs, in a greedy fashion, an encoding of the data. This encoding can be seen as an embedding into a space, where a weighted Hamming distance is correlated with the unknown similarity. This allows us to predict when two previously unseen examples are similar and, importantly, to efficiently search a very large database for examples similar to a query. This approach is tested on a set of standard machine learning benchmark problems. The model of similarity learned with our algorithm provides and improvement over standard example-based classification and regression. We also apply this framework to problems in computer vision: articulated pose estimation of humans from single images...

In the eye of an expert: Conveying perceptual skills in biological and medical domains via eye movement modeling examples; Im Auge des Experten: Vermittlung perzeptueller Fertigkeiten in biologischen und medizinischen Domänen via Blickbewegungsmodelbeispielen

Jarodzka, Halszka
Tipo: Dissertação
EN
Relevância na Pesquisa
45.84%

Realism and Control Problem-based learning programs as a data source for work-related research

Zolin, Roxanne; Fruchter, Renate; Levitt, Raymond E.
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
45.81%
Problem-based learning (PBL) is a pedagogical methodology that presents the learner with a problem to be solved to stimulate and situate learning. This paper presents key characteristics of a problem-based learning environment that determines its suitability as a data source for work-related research studies. To date, little has been written about the availability and validity of PBL environments as a data source and its suitability for work-related research. We describe problem-based learning and use a research project case study to illustrate the challenges associated with industry work samples. We then describe the PBL course used in our research case study and use this example to illustrate the key attributes of problem-based learning environments and show how the chosen PBL environment met the work-related research requirements of the research case study. We propose that the more realistic the PBL work context and work group composition, the better the PBL environment as a data source for a work-related research. The work context is more realistic when relevant and complex project-based problems are tackled in industry-like work conditions over longer time frames. Work group composition is more realistic when participants with industry-level education and experience enact specialized roles in different disciplines within a professional community.

Integrating collaborative concept mapping in case based learning

Tifi, Alfredo
Tipo: Artigo de Revista Científica
ENG
Relevância na Pesquisa
65.78%
Different significance of collaborative concept mapping and collaborative argumentation in Case Based Learning are discussed and compared in the different perspectives of answering focus questions, of fostering reflective thinking skills and in managing uncertainty in problem solving in a scaffolded environment. Marked differences are pointed out between the way concepts are used in constructing concept maps and the way meanings are adopted in case-based learning through guided argumentation activities. Shared concept maps should be given different scopes, as for example a) as an advance organizer in preparing a background system of concepts that will undergo transformation while accompanying the inquiry activities on case studies or problems; b) together with narratives, to enhance awareness of the situated epistemologies that are being entailed in choosing certain concepts during more complex case studies, and c) after-learning construction of a holistic vision of the whole domain by means of the most inclusive concepts, while scaffolded- collaborative writing of narratives and arguments in describing-treating cases could better serve as a source of situated-inspired tools to create-refine meanings for particular concepts.; El mapeo conceptual y la argumentaci??n colaborativa son utilizados en la estrategia de estudios de caso con la ayuda de andamiajes conceptuales. Se discute y comparan las respuestas que los estudiantes dan a las preguntas de enfoque...

Teoría de modelado del e-learning y aplicación a un sistema de pistas adaptativo en tutoría inteligente utilizando técnicas de web semántica

Muñoz Merino, Pedro José
Tipo: info:eu-repo/semantics/doctoralThesis; info:eu-repo/semantics/doctoralThesis Formato: application/pdf
SPA
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45.88%
El e-learning es un factor clave en la actual sociedad de la información. El poder habilitar las mejores prácticas de enseñanza a través de las tecnologías de la información para posibilitar un aprendizaje más efectivo para los alumnos, así como proporcionar un sencillo y flexible acceso a todas las potencialidades para los profesores, al mismo tiempo que se maximiza la eficiencia y adecuación de su implementación usando las tecnologías de la información, supone un reto en el que hay que tener en cuenta multitud de variables y factores. Ello engloba las teorías tradicionales de aprendizaje en aula, pero también muchos nuevos aspectos que surgen o se enfatizan por el uso de las tecnologías de la información. Numerosas investigaciones se han llevado a cabo para el avance en esta materia. Tales investigaciones se centran por lo general en aspectos específicos, pero no obstante creemos también necesaria una teoría de modelado del e-learning integradora de diferentes variables y aspectos involucrados para poder comprender mejor esta materia tan compleja, así como cubrir ciertas carencias específicas de modelado para la conformación de dicha teoría. En esta tesis se proporciona una teoría de modelado del e-learning...

The internet as a learning tool for effective project based learning in the teaching of the geography primary curriculum

O'Sullivan, Fiona
Fonte: University of Limerick, Department of Education and Professional Studies Publicador: University of Limerick, Department of Education and Professional Studies
Tipo: Master thesis (Taught); all_ul_research; ul_theses_dissertations; none
ENG
Relevância na Pesquisa
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non-peer-reviewed; The purpose of this study is to examine the effectiveness of the Internet, as a resource for Project Based Learning (PBL) in the teaching of the Geography Primary Curriculum. We can clearly see the influence of new technology on society. Over the past two decades there has been a massive transformation in the way we access, research, process and transfer information. The Internet is a positive resource, with the power to transform schools and revolutionise children’s learning. The Department of Education and Science have shown their support for the use of the Internet through the increased availability of Broadband in Primary Schools. They have also provided increased opportunities for teacher’s professional development in the use of the Internet for teaching and learning. This research study will involve 6th class students from a Dublin Primary School, to use the Internet to search for information for a Geography project. This project will be based on the strand Human Environments and the strand unit; People Living and Working in a Contrasting Part of Ireland and People and Other Lands, from the Geography Primary Curriculum. The three countries involved in this research will include the United Kingdom, Japan and America. Students will participate in this research...

Aprendizagem baseada na investigação : a experiência do NIED/Unicamp na Escola Elza Maria Pellegrini, em Campinas - 2013; Inquiry-based learning : the experience of NIED/Unicamp in the School Elza Maria Pellegrini, in Campinas - 2013

Maísa Maryelli de Oliveira
Fonte: Biblioteca Digital da Unicamp Publicador: Biblioteca Digital da Unicamp
Tipo: Dissertação de Mestrado Formato: application/pdf
Relevância na Pesquisa
65.79%

Interações tutor-aluno analisadas através de seus estados mentais; Tutor/student interactions analyzed through their mental states

Moussalle, Neila Maria
Tipo: Dissertação Formato: application/pdf
POR
Relevância na Pesquisa
45.81%

Learning and Example Selection for Object and Pattern Detection

Sung, Kah-Kay
Fonte: MIT - Massachusetts Institute of Technology Publicador: MIT - Massachusetts Institute of Technology
Formato: 195 p.; 20467529 bytes; 2831164 bytes; application/postscript; application/pdf
EN_US
Relevância na Pesquisa
55.98%
This thesis presents a learning based approach for detecting classes of objects and patterns with variable image appearance but highly predictable image boundaries. It consists of two parts. In part one, we introduce our object and pattern detection approach using a concrete human face detection example. The approach first builds a distribution-based model of the target pattern class in an appropriate feature space to describe the target's variable image appearance. It then learns from examples a similarity measure for matching new patterns against the distribution-based target model. The approach makes few assumptions about the target pattern class and should therefore be fairly general, as long as the target class has predictable image boundaries. Because our object and pattern detection approach is very much learning-based, how well a system eventually performs depends heavily on the quality of training examples it receives. The second part of this thesis looks at how one can select high quality examples for function approximation learning tasks. We propose an {em active learning} formulation for function approximation, and show for three specific approximation function classes, that the active example selection strategy learns its target with fewer data samples than random sampling. We then simplify the original active learning formulation...

Learning Games and Rademacher Observations Losses

Nock, Richard
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
55.98%
It has recently been shown that supervised learning with the popular logistic loss is equivalent to optimizing the exponential loss over sufficient statistics about the class: Rademacher observations (rados). We first show that this unexpected equivalence can actually be generalized to other example / rado losses, with necessary and sufficient conditions for the equivalence, exemplified on four losses that bear popular names in various fields: exponential (boosting), mean-variance (finance), Linear Hinge (on-line learning), ReLU (deep learning), and unhinged (statistics). Second, we show that the generalization unveils a surprising new connection to regularized learning, and in particular a sufficient condition under which regularizing the loss over examples is equivalent to regularizing the rados (with Minkowski sums) in the equivalent rado loss. This brings simple and powerful rado-based learning algorithms for sparsity-controlling regularization, that we exemplify on a boosting algorithm for the regularized exponential rado-loss, which formally boosts over four types of regularization, including the popular ridge and lasso, and the recently coined slope --- we obtain the first proven boosting algorithm for this last regularization. Through our first contribution on the equivalence of rado and example-based losses...

Theoretical Analyses of Cross-Validation Error and Voting in Instance-Based Learning

Turney, Peter D.
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
55.87%
This paper begins with a general theory of error in cross-validation testing of algorithms for supervised learning from examples. It is assumed that the examples are described by attribute-value pairs, where the values are symbolic. Cross-validation requires a set of training examples and a set of testing examples. The value of the attribute that is to be predicted is known to the learner in the training set, but unknown in the testing set. The theory demonstrates that cross-validation error has two components: error on the training set (inaccuracy) and sensitivity to noise (instability). This general theory is then applied to voting in instance-based learning. Given an example in the testing set, a typical instance-based learning algorithm predicts the designated attribute by voting among the k nearest neighbors (the k most similar examples) to the testing example in the training set. Voting is intended to increase the stability (resistance to noise) of instance-based learning, but a theoretical analysis shows that there are circumstances in which voting can be destabilizing. The theory suggests ways to minimize cross-validation error, by insuring that voting is stable and does not adversely affect accuracy.; Comment: 48 pages

Logical settings for concept learning from incomplete examples in First Order Logic

Bouthinon, Dominique; Soldano, Henry; Ventos, Véronique
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
45.87%
We investigate here concept learning from incomplete examples. Our first purpose is to discuss to what extent logical learning settings have to be modified in order to cope with data incompleteness. More precisely we are interested in extending the learning from interpretations setting introduced by L. De Raedt that extends to relational representations the classical propositional (or attribute-value) concept learning from examples framework. We are inspired here by ideas presented by H. Hirsh in a work extending the Version space inductive paradigm to incomplete data. H. Hirsh proposes to slightly modify the notion of solution when dealing with incomplete examples: a solution has to be a hypothesis compatible with all pieces of information concerning the examples. We identify two main classes of incompleteness. First, uncertainty deals with our state of knowledge concerning an example. Second, generalization (or abstraction) deals with what part of the description of the example is sufficient for the learning purpose. These two main sources of incompleteness can be mixed up when only part of the useful information is known. We discuss a general learning setting, referred to as "learning from possibilities" that formalizes these ideas...

Rapid Learning with Stochastic Focus of Attention

Pelossof, Raphael; Ying, Zhiliang
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
45.89%
We present a method to stop the evaluation of a decision making process when the result of the full evaluation is obvious. This trait is highly desirable for online margin-based machine learning algorithms where a classifier traditionally evaluates all the features for every example. We observe that some examples are easier to classify than others, a phenomenon which is characterized by the event when most of the features agree on the class of an example. By stopping the feature evaluation when encountering an easy to classify example, the learning algorithm can achieve substantial gains in computation. Our method provides a natural attention mechanism for learning algorithms. By modifying Pegasos, a margin-based online learning algorithm, to include our attentive method we lower the number of attributes computed from $n$ to an average of $O(\sqrt{n})$ features without loss in prediction accuracy. We demonstrate the effectiveness of Attentive Pegasos on MNIST data.

Dynamic learning from multiple examples for semantic object segmentation and search

Xu, Y; Saber, Eli; Tekalp, A.
Fonte: Elsevier Science Publicador: Elsevier Science
Tipo: Postprint
EN_US
Relevância na Pesquisa
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We present a novel ‘‘dynamic learning’’ approach for an intelligent image database system to automatically improve object segmentation and labeling without user intervention, as new examples become available, for object-based indexing. The proposed approach is an extension of our earlier work on ‘‘learning by example,’’ which addressed labeling of similar objects in a set of database images based on a single example. The proposed dynamic learning procedure utilizes multiple example object templates to improve the accuracy of existing object segmentations and labels. Multiple example templates may be images of the same object from different viewing angles, or images of related objects. This paper also introduces a new shape similarity metric called normalized area of symmetric differences (NASD), which has desired properties for use in the proposed ‘‘dynamic learning’’ scheme, and is more robust against boundary noise that results from automatic image segmentation. Performance of the dynamic learning procedures has been demonstrated by experimental results.; Journal Webpage: http://www.elsevier.com/wps/find/journaldescription.cws_home/622809/description#description; RIT community members may access full-text via RIT Libraries licensed databases: http://library.rit.edu/databases/

Developing an example-based faculty training course

Vignare, Karen; Trippe, Anthony
Fonte: The Eighth Sloan-C International Conference on Asynchronous Learning Networks (ALN): The Power of Online Learning: The Faculty Experience. Publicador: The Eighth Sloan-C International Conference on Asynchronous Learning Networks (ALN): The Power of Online Learning: The Faculty Experience.
Tipo: Relatório Formato: 77422 bytes; application/pdf
EN_US
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Developing an example-based faculty training course Karen K. Vignare Anthony P. Trippe Rochester Institute of Technology Abstract In an effort to attract and retain students, higher education distance learning organizations are coming to realize the importance of faculty training and support. Research has shown that one of the factors highly correlated to student retention in the online environment is faculty performance. (1) It is generally accepted that there is also a connection between student satisfaction with faculty performance and student learning. (2) (3) Student satisfaction rises when students are challenged by the faculty and interested in the material. The presence of knowledgeable, experienced, personable, confident and most importantly well-trained faculty creates a classroom environment which produces student interaction and ultimately leads to a high level of student satisfaction with the entire learning experience. This paper/presentation describes lessons learned in the development of a faculty training course intended for faculty who plan to present their first online course. The course detailed in this paper is based upon the principle of placing the new faculty member in the role of a student. Typical students are motivated and they are adults. We tell students...

Designing a Web-based Interface for Student Peer Review on a Unix Server

Duke, Joshua M.; Whisler, Jeff
Fonte: Department of Applied Economics and Statistics, University of Delaware, Newark, DE. Publicador: Department of Applied Economics and Statistics, University of Delaware, Newark, DE.
Tipo: Relatório
EN_US
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This report describes an application of and the procedures for developing a web-based interface on a Unix server, using a simple guestbook program. The advantage of the guestbook platform is that it is commonly available on college campuses and can be secured. The application facilitates problem-based learning and other active-learning goals in an undergraduate seminar in environmental law. This report provides an example of the application and reviews the programming necessary to accomplish the learning goals.; The Institute for Transforming Undergraduate Education and The Present???s Technological Assistance Grant, both from The University of Delaware