scispace - formally typeset
Search or ask a question
Institution

French Institute for Research in Computer Science and Automation

GovernmentLe Chesnay, France
About: French Institute for Research in Computer Science and Automation is a government organization based out in Le Chesnay, France. It is known for research contribution in the topics: Context (language use) & Population. The organization has 13012 authors who have published 38653 publications receiving 1318995 citations. The organization is also known as: INRIA & Institute for national research in information science and automatic control.


Papers
More filters
Journal ArticleDOI
01 Aug 1996
TL;DR: Three new ideas for solving the problem of achieving real‐time performance for these models of 3D solid volumetric Finite Element models to surgery simulation are introduced.
Abstract: This paper discusses the application of 3D solid volumetric Finite Element models to surgery simulation. In particular it introduces three new ideas for solving the problem of achieving real-time performance for these models. The simulation system we have developed is described and we demonstrate real-time deformation using the methods developed in the paper.

589 citations

Posted Content
TL;DR: This paper converts the dense weight matrices of the fully-connected layers to the Tensor Train format such that the number of parameters is reduced by a huge factor and at the same time the expressive power of the layer is preserved.
Abstract: Deep neural networks currently demonstrate state-of-the-art performance in several domains. At the same time, models of this class are very demanding in terms of computational resources. In particular, a large amount of memory is required by commonly used fully-connected layers, making it hard to use the models on low-end devices and stopping the further increase of the model size. In this paper we convert the dense weight matrices of the fully-connected layers to the Tensor Train format such that the number of parameters is reduced by a huge factor and at the same time the expressive power of the layer is preserved. In particular, for the Very Deep VGG networks we report the compression factor of the dense weight matrix of a fully-connected layer up to 200000 times leading to the compression factor of the whole network up to 7 times.

588 citations

Proceedings ArticleDOI
01 May 2001
TL;DR: In this article, the authors describe an attempt at the construction of such algorithms and its implementation using a combination of data structures, application-specific caching policies, and application specific query processing, which can handle 600 events per second for a typical workload containing 6 million subscriptions.
Abstract: Publish/Subscribe is the paradigm in which users express long-term interests (“subscriptions”) and some agent “publishes” events (e.g., offers). The job of Publish/Subscribe software is to send events to the owners of subscriptions satisfied by those events. For example, a user subscription may consist of an interest in an airplane of a certain type, not to exceed a certain price. A published event may consist of an offer of an airplane with certain properties including price. Each subscription consists of a conjunction of (attribute, comparison operator, value) predicates. A subscription closely resembles a trigger in that it is a long-lived conditional query associated with an action (usually, informing the subscriber). However, it is less general than a trigger so novel data structures and implementations may enable the creation of more scalable, high performance publish/subscribe systems. This paper describes an attempt at the construction of such algorithms and its implementation. Using a combination of data structures, application-specific caching policies, and application-specific query processing our system can handle 600 events per second for a typical workload containing 6 million subscriptions.

587 citations

Journal ArticleDOI
TL;DR: In this paper, the authors revisited the concepts of Jacobian matrix, manipulability and condition number for parallel robots as accuracy indices in view of optimal design and showed that their real significance is not always well understood.
Abstract: Although the concepts of Jacobian matrix, manipulability, and condition number have existed since the very early beginning of robotics their real significance is not always well understood. In this paper we revisit these concepts for parallel robots as accuracy indices in view of optimal design. We first show that the usual Jacobian matrix derived from the input-output velocities equations may not be sufficient to analyze the positioning errors of the platform. We then examine the concept of manipulability and show that its classical interpretation is erroneous. We then consider various common local dexterity indices, most of which are based on the condition number of the Jacobian matrix. It is emphasized that even for a given robot in a particular pose there are a variety of condition numbers and that their values are not coherent between themselves but also with what we may expect from an accuracy index. Global conditioning indices are then examined. Apart from the problem of being based on the local accuracy indices that are questionable, there is a computational problem in their calculation that is neglected most of the time. Finally, we examine what other indices may be used for optimal design and show that their calculation is most challenging.

587 citations

Journal ArticleDOI
TL;DR: The current practices in the information visualization research community are encapsulated and a different approach is provided to reaching decisions about what might be the most effective evaluation of a given information visualization.
Abstract: We take a new, scenario-based look at evaluation in information visualization. Our seven scenarios, evaluating visual data analysis and reasoning, evaluating user performance, evaluating user experience, evaluating environments and work practices, evaluating communication through visualization, evaluating visualization algorithms, and evaluating collaborative data analysis were derived through an extensive literature review of over 800 visualization publications. These scenarios distinguish different study goals and types of research questions and are illustrated through example studies. Through this broad survey and the distillation of these scenarios, we make two contributions. One, we encapsulate the current practices in the information visualization research community and, two, we provide a different approach to reaching decisions about what might be the most effective evaluation of a given information visualization. Scenarios can be used to choose appropriate research questions and goals and the provided examples can be consulted for guidance on how to design one's own study.

583 citations


Authors

Showing all 13078 results

NameH-indexPapersCitations
Cordelia Schmid135464103925
Bernt Schiele13056870032
Francis Bach11048454944
Jian Sun109360239387
Pascal Fua10261449751
Nicholas Ayache9762443140
Olivier Bernard9679037878
Laurent D. Cohen9441742709
Peter Sturm9354839119
Guy Orban9345526178
Sebastien Ourselin91111634683
François Fleuret9193642585
Katrin Amunts8943835069
Tamer Basar8897734903
Nassir Navab88137541537
Network Information
Related Institutions (5)
Microsoft
86.9K papers, 4.1M citations

94% related

Google
39.8K papers, 2.1M citations

93% related

Carnegie Mellon University
104.3K papers, 5.9M citations

93% related

Eindhoven University of Technology
52.9K papers, 1.5M citations

90% related

Polytechnic University of Catalonia
45.3K papers, 949.3K citations

90% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202328
2022149
20211,374
20201,499
20191,637
20181,597