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Institution

Orange S.A.

CompanyParis, France
About: Orange S.A. is a company organization based out in Paris, France. It is known for research contribution in the topics: Terminal (electronics) & Signal. The organization has 6735 authors who have published 9190 publications receiving 156440 citations. The organization is also known as: Orange SA & France Télécom.


Papers
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Journal ArticleDOI
TL;DR: This paper proposes scalable admission and congestion control schemes that allow each base station to decide independently of the others what set of voice users to serve and/or what bit rates to offer to elastic traffic users competing for bandwidth.
Abstract: This paper proposes scalable admission and congestion control schemes that allow each base station to decide independently of the others what set of voice users to serve and/or what bit rates to offer to elastic traffic users competing for bandwidth. These algorithms are primarily meant for large CDMA networks with a random but homogeneous user distribution. They take into account in an exact way the influence of geometry on the combination of inter-cell and intra-cell interferences as well as the existence of maximal power constraints of the base stations and users. We also study the load allowed by these schemes when the size of the network tends to infinity and the mean bit rate offered to elastic traffic users. By load, we mean here the number of voice users that each base station can serve.

38 citations

Journal ArticleDOI
TL;DR: The robustness of the estimation against noise is studied, both theoretically and experimentally, and the performance is assessed in comparison with two state-of-the-art algorithms: an unmodified version of the reassignment method and a quadratically interpolated fast Fourier transform method.
Abstract: This paper proposes an extension of the applicability of phase-vocoder-based frequency estimators for generalized sinusoidal models, which include phase and amplitude modulations. A first approach, called phase corrected vocoder (PCV), takes into account the modification of the Fourier phases resulting from these modulations. Another approach is based on an adaptation of the principles of the time-frequency reassignment and is referred to as the reassigned vocoder (RV). The robustness of the estimation against noise is studied, both theoretically and experimentally, and the performance is assessed in comparison with two state-of-the-art algorithms: an unmodified version of the reassignment method and a quadratically interpolated fast Fourier transform method (QIFFT).

38 citations

Journal ArticleDOI
TL;DR: The concept of list signatures is introduced as a variant of group signatures which sets a limit on the number of signatures each group member may issue, and the problem of publicly identifying group members who exceed their limits is considered.

38 citations

Proceedings ArticleDOI
19 Apr 2009
TL;DR: The behavior of the Internet in the absence of congestion control is characterized, and the efficiency of resource utilization is estimated in terms of the maximum load the network can sustain, accounting for the random nature of traffic.
Abstract: In this paper we seek to characterize the behavior of the Internet in the absence of congestion control. More specifically, we assume all sources transmit at their maximum rate and recover from packet loss by the use of some ideal erasure coding scheme. We estimate the efficiency of resource utilization in terms of the maximum load the network can sustain, accounting for the random nature of traffic. Contrary to common belief, there is generally no congestion collapse. Efficiency remains higher than 90% for most network topologies as long as maximum source rates are less than link capacity by one or two orders of magnitude. Moreover, a simple fair drop policy enforcing fair sharing at flow level is sufficient to guarantee 100% efficiency in all cases.

38 citations

Proceedings Article
02 May 2016
TL;DR: An online random forest algorithm is proposed to address the contextual bandit problem, based on the sample complexity needed to find the optimal decision stump, and it is shown that the proposed algorithm is optimal up to logarithmic factors.
Abstract: To address the contextual bandit problem, we propose an online random forest algorithm. The analysis of the proposed algorithm is based on the sample complexity needed to find the optimal decision stump. Then, the decision stumps are recursively stacked in a random collection of decision trees, BANDIT FOREST. We show that the proposed algorithm is optimal up to logarithmic factors. The dependence of the sample complexity upon the number of contextual variables is logarithmic. The computational cost of the proposed algorithm with respect to the time horizon is linear. These analytical results allow the proposed algorithm to be efficient in real applications, where the number of events to process is huge, and where we expect that some contextual variables, chosen from a large set, have potentially non-linear dependencies with the rewards. In the experiments done to illustrate the theoretical analysis, BANDIT FOREST obtain promising results in comparison with state-of-the-art algorithms.

38 citations


Authors

Showing all 6762 results

NameH-indexPapersCitations
Patrick O. Brown183755200985
Martin Vetterli10576157825
Samy Bengio9539056904
Aristide Lemaître7571222029
Ifor D. W. Samuel7460523151
Mischa Dohler6835519614
Isabelle Sagnes6775318178
Jean-Jacques Quisquater6533518234
David Pointcheval6429819538
Emmanuel Dupoux6326714315
David Gesbert6345624569
Yonghui Li6269715441
Sergei K. Turitsyn6172214063
Joseph Zyss6143417888
Jean-Michel Gérard5842114896
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20238
20225
20215
20205
201915
201814