Institution
INESC-ID
Nonprofit•Lisbon, Portugal•
About: INESC-ID is a nonprofit organization based out in Lisbon, Portugal. It is known for research contribution in the topics: Computer science & Context (language use). The organization has 932 authors who have published 2618 publications receiving 37658 citations.
Topics: Computer science, Context (language use), Field-programmable gate array, Control theory, Adaptive control
Papers published on a yearly basis
Papers
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TL;DR: A VR environment where user interactions are supported by untethered, easy to operate, peripherals, using a mobile virtual reality headset to provide virtual immersion and simplified geometric information to create voxel-based maquettes is developed.
60 citations
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20 Oct 2014
TL;DR: Teachers saw a role for the tutor in acting as an engaging tool for all, preferably in groups, and gathering information about students' learning progress without taking over the teachers' responsibility for the actual assessment.
Abstract: In this paper, we describe the results of an interview study conducted across several European countries on teachers' views on the use of empathic robotic tutors in the classroom. The main goals of the study were to elicit teachers' thoughts on the integration of the robotic tutors in the daily school practice, understanding the main roles that these robots could play and gather teachers' main concerns about this type of technology. Teachers' concerns were much related to the fairness of access to the technology, robustness of the robot in students' hands and disruption of other classroom activities. They saw a role for the tutor in acting as an engaging tool for all, preferably in groups, and gathering information about students' learning progress without taking over the teachers' responsibility for the actual assessment. The implications of these results are discussed in relation to teacher acceptance of ubiquitous technologies in general and robots in particular.
60 citations
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12 May 2008TL;DR: In this article, the authors evaluate and compare the user enjoyment when playing a game of chess in two situations: against a physically embodied robotic agent and against a virtually embodied agent, displayed on screen.
Abstract: This paper presents an experiment that evaluates and compares the user enjoyment when playing a game of chess in two situations: against a physically embodied robotic agent and against a virtually embodied agent, displayed on screen. The results of the study suggest that embodiment has implications on user enjoyment, as the experience against a robotic agent was classified as more enjoyable than against a virtually embodied agent.
60 citations
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TL;DR: This work presents an on-line system designed to behave as a virtual therapist incorporating automatic speech recognition technology that permits aphasia patients to perform word naming training exercises and focuses on the study of the automatic word naming detector module.
60 citations
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09 Jul 2008TL;DR: A new algorithm for probabilistic multi-view learning which uses the idea of stochastic agreement between views as regularization and performs better than CoBoosting and two-view Perceptron on several flat and structured classification problems.
Abstract: In many machine learning problems, labeled training data is limited but unlabeled data is ample. Some of these problems have instances that can be factored into multiple views, each of which is nearly sufficent in determining the correct labels. In this paper we present a new algorithm for probabilistic multi-view learning which uses the idea of stochastic agreement between views as regularization. Our algorithm works on structured and unstructured problems and easily generalizes to partial agreement scenarios. For the full agreement case, our algorithm minimizes the Bhattacharyya distance between the models of each view, and performs better than CoBoosting and two-view Perceptron on several flat and structured classification problems.
59 citations
Authors
Showing all 967 results
Name | H-index | Papers | Citations |
---|---|---|---|
João Carvalho | 126 | 1278 | 77017 |
Jaime G. Carbonell | 72 | 496 | 31267 |
Chris Dyer | 71 | 240 | 32739 |
Joao P. S. Catalao | 68 | 1039 | 19348 |
Muhammad Bilal | 63 | 720 | 14720 |
Alan W. Black | 61 | 413 | 19215 |
João Paulo Teixeira | 60 | 636 | 19663 |
Bhiksha Raj | 51 | 359 | 13064 |
Joao Marques-Silva | 48 | 289 | 9374 |
Paulo Flores | 48 | 321 | 7617 |
Ana Paiva | 47 | 472 | 9626 |
Miadreza Shafie-khah | 47 | 450 | 8086 |
Susana Cardoso | 44 | 400 | 7068 |
Mark J. Bentum | 42 | 226 | 8347 |
Joaquim Jorge | 41 | 290 | 6366 |