Journée Optim & Telecoms (10 avril 2015)

 
"Optim & Télécoms",

Vendredi 10 avril 2015

Amphi Copernic, Sup'Galilée

Université de Paris 13

99, Av J-B, Clément, 93430 Villetaneuse

 

 

Le Pôle Math-STIC de l'université Paris 13 organise le vendredi 10 avril 2015 une journée scientifique intitulée Optim&Télécoms. Ci-dessous le programme de la journée. La participation à la journée et gratuite ; une inscription est néanmoins requise pour des raisons de logistique, merci donc d'envoyer un This email address is being protected from spambots. You need JavaScript enabled to view it. aux organisateurs pour confirmer votre participation. N'hésitez pas à diffuser cet appel auprès de vos collègues.
 

Résumé :
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Les techniques d'optimisation ont souvent été un outil indispensable dans les réseaux de télécommunications, et ce dans toutes les étapes de conception, de planification, de dimensionnement et de déploiement.
Aussi, le but de cette journée "Optim & Télécoms" est de donner un aperçu des travaux de recherches associant optimisation et réseaux de télécommunications. Les problématiques concernées seront généralement définies aussi bien d'un point de vue opérateur (capacité, coûts, etc.) que d'un point de vue usager (QdS - Qualité de Service) et ce au niveau de toutes les couches réseaux (routage, allocation de ressource, récepteurs radio, etc.) Cette journée sera en outre l'occasion d'échanges entre chercheurs, universitaires et industriels autour de ces thématiques.
 

Programme :
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9h00: Ouverture de la journée

09h15-10h15, "Multi-objective Optimization for 5G Networks", Mérouane Debbah, Mathematical and Algorithmic Sciences Lab, Huawei, France

10h15-11h00: "Distributed Load Balancing in Heterogeneous Networks", Marceau Coupechoux, Telecom ParisTech, France

11h00-11h30 Pause café

11h30-12h00: "The Conflicting Power and Delay Optimization in Wireless Access Networks", Farah Moety, ORANGE Labs Networks, Issy-Les-Moulineaux, France

12h00-14h00 Déjeuner (Salle B407, laboratoire LAGA)

14h00-14h30 : "Conception de Réseaux Fiables de Télécommunications et de Réseaux Privés Virtuels", Diarrassouba Ibrahima, Laboratoire LMAH, Université du Havre, France

14h30-15h00 : "Assessment of energy savings in real-world cellular networks", Diala Naboulsi, INSA-Lyon, CITI-INRIA Urbanet, France

15h00-15h30 Pause café

15h30-16h00 : "Allocation optimisée de ressources radio pour les flux à forte contrainte de délai", Marwen Abdennebi, Laboratoire L2TI, Université Paris 13, France


Lieu :
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Amphi Copernic, Sup'Galilée

Université de Paris 13

99, Av J-B, Clément, 93430 Villetaneuse

 
Accès :
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http://www.sup-galilee.univ-paris13.fr/index.php?option=com_content&task=view&id=132&Itemid=121
 
 
Organisation :
==============
Marwen Abdennebi, This email address is being protected from spambots. You need JavaScript enabled to view it.
Nadjib Achir, This email address is being protected from spambots. You need JavaScript enabled to view it.
L2TI, Université de Paris 13

Journée "Big Data - Vision globale" (26 mars 2015)

Journée du pôle Math-Stic - Big Data - Vision globale
Amphi Euler - Institut Galilée

Université Paris 13
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Accès : voir le plan https://lipn.univ-paris13.fr/fr/laboratoire/contact#campus

Pour s'inscrire merci de remplir le formulaire : https://docs.google.com/forms/d/1r0uxxnzMzOWCqiny_qCx9ZlOLgUfEBkrjl-XmRdgowk/viewform?usp=send_form

 

Read more: Journée "Big Data - Vision globale" (26 mars 2015)

Journée "optimisation et traitement automatique des langues" (16 décembre 2013)

Les méthodes d'optimisation sont de plus en plus utilisées en traitement automatique des langues pour concevoir des méthodes efficaces tant pour l'apprentissage de modèles que pour le décodage, notamment en offrant un cadre formel qui distingue clairement les contraintes globales des contraintes locales, tout en permettant de les combiner.

L'équipe RCLN du Laboratoire d'Informatique de Paris Nord s'intéresse de près à ces méthodes pour la modélisation conjointe des différents niveaux de description linguistique. Dans le cadre du pôle math/stic de Paris 13, avec le soutien du LABEX EFL, et en collaboration avec l'équipe AOC du LIPN, l'équipe RCLN organise une journée de séminaires autour des thèmes de l'optimisation et du traitement automatique des langues.

Cette journée aura lieu sur le campus de l'Université Paris 13 à Villetaneuse, dans l'amphithéâtre Euler.

  • 09h30-10h00 :: Accueil (Amphi Euler)
  • 10h00-11h00 :: Exposé d'André Martins (Amphi Euler)
  • 11h15-12h15 :: Exposé de Sebastian Riedel (Amphi Euler)
  • Pause déjeuner (LIPN)
  • 13h45-14h45 :: Exposé de Xavier Carreras (Amphi Euler)
  • 15h00-16h00 :: Exposé de Joseph Le Roux (Amphi Euler)
  • 16h00 :: goûter au LIPN !

La participation à cette journée est libre. Si vous comptez y assister, nous vous demandons, pour des raisons pratiques (organisation du buffet notamment), de nous l'indiquer à cette adresse : http://doodle.com/87mnbcdbzdmytffc.

Résumé des quatre exposés prévus :

  • André Martins, Priberam, Lisbon

Title: AD3: A New Decoder for Structured Prediction

Abstract: In this talk, I will present AD3 ("Alternating Directions Dual Decomposition"), a new consensus-based decoder for problems representable as factor graphs. AD3 is an approximate decoder that ignores global effects caused by the cycles of the graph, solving a linear relaxation of the original problem. It can handle many scenarios often encountered in NLP and IR applications, such as models with constraints in first-order logic; models involving budget or knapsack constraints; and combinations of structured models which are individually tractable, but hard to decode jointly. Like other dual decomposition algorithms, AD3 has a modular architecture, where local subproblems are solved independently, and their solutions are gathered to compute a global update. The key characteristic of AD3 is that each local subproblem has a quadratic regularizer, leading to faster convergence (both theoretically and in practice). After providing closed-form solutions for several of these subproblems, I will proceed to discuss a recent active set method that works for arbitrary factors, requiring only a local maximization oracle (the same oracle required in subgradient-based dual decomposition). In the second part of the talk, I will discuss two recent applications of AD3 in NLP problems: dependency parsing and compressive summarization. I will present "Turbo Parser," an open source dependency parser, which was recently improved with AD3 and the active set method to permit fast decoding of non-projective third-order models. Experiments in 14 languages yield state-of-art results, with parsing speeds ranging between 700 and 4,000 tokens per second. For compressive summarization, the use of AD3 leads to a system which is modular in the three qualities that define a good summary (conciseness, informativeness, and grammaticality), with state-of-the-art ROUGE scores, and runtimes close to extractive summarizers. This work was done in collaboration with Noah Smith, Mário Figueiredo, Eric Xing, Pedro Aguiar, and Miguel Almeida.

  • Sebastian Riedel, UCL, London.

Title: Predict, Price and Cut: Column and Row Generation for Structured Prediction

Abstract: Many problems in NLP, and structured prediction in general, can be cast as finding high-scoring structures based on a large set of candidate parts. For example, In second order tagging, we have to select high-scoring transitions between tags in a globally consistent fashion. In second order graph-based dependency parsing we have to choose a quadratic number of first order and a cubic number of second order edges such that the graph is both high-scoring and a tree. What makes such problems challenging is the large number of possible parts to consider. This number not only affects the cost of search or optimization but also slows down the process of scoring parts before they enter the optimisation problem, and extracting features. In this talk I present an approach that can solve problems with large sets of candidate parts without considering all of these parts in either optimization or scoring. In contrast to most pruning heuristics, our algorithm can give certificates of optimality before having optimized over, or even scored, all parts. It does so without the need of auxiliary models or tuning of threshold parameters. This is achieved by a delayed column and row generation algorithm that iteratively solves an LP relaxation over a small subset of current candidate parts, and then finds new candidates with high scores that can be inserted into the current optimal solution without removing high scoring existing structure. The latter step subtracts from the cost of a part the price of resources the part requires, and is often referred as pricing. Sometimes parts may score highly after pricing, but are necessary in order to make the current solution feasible. We add such parts in a step that roughly amounts to violated cuts to the LP. We evaluate our approach on two applications: second order dependency parsing and first order tagging with large domains. In both cases we dramatically reduce the number of parts considered, and observe about an order of magnitude speed-up. This is possible without loss of optimality guarantees, and hence accuracy.

  • Xavier Carreras, UPC, Barcelona

Title: Learning Automata and Grammars: From Spectral Algorithms to Convex Optimizations

Abstract: There is an increasing interest in spectral methods to learn latent-variable language models in the form of weighted automata and context-free grammars. Spectral methods provide an algebraic formulation to the problem of inducing automata or grammars from data, and directly exploit the recurrence relations behind the model. I will review the spectral method from an algebraic perspective, making use of Hankel matrices as the key object behind the method: a Hankel matrix collects all necessary statistics of the distribution we want to learn; and finding a low-rank factorization of this matrix results in the automata or grammar. Under mild assumptions, it can be shown that this method nicely approximates the target model. From here, I will show how we can reformulate the spectral learning algorithm as a low-rank convex optimization. This will be useful to adapt the method to other settings, by adding linear constraints. I will focus in "unsupervised" induction of context-free grammars, that is, learning a grammar from plain strings. Our formulation involves optimizing for a low-rank Hankel matrix that is linearly constrained to satisfy inside-outside recursions. An analogous method method can be formulated to learn finite-state transducers from unaligned parallel strings.

  • Joseph Le Roux, LIPN, Paris

Title: Combining PCFG-LA Models with Dual Decomposition: A case Study with Function Labels and Binarization

Abstract: It has recently been shown that different NLP models can be effectively combined using dual decomposition. In this talk, we present how PCFG-LAs (Probabilistic Context-Free Grammars with Latent Annotations, the state-of-the-art model for unlexicalized constituent parsing) are suitable for combination in this way. We first show how the intractable problem of exact PCFG-LA decoding is approximated with anchored PCFGs. Then we present a method for combining anchored PCFGs based on the partial superposition of tree structures. We experiment with the different models which result from alternative methods of extracting a grammar from a treebank (retaining or discarding function labels, left binarization versus right binarization) and achieve state-of-the-art parsing performance, with a labeled Parseval F-score of 92.4 on Wall Street Journal Section 23 – this represents an error reduction rate of 7% over a strong PCFG-LA product-model baseline. This work was done in collaboration with Antoine Rozenknop and Jennifer Foster.

Journée "Images et Signaux" (18 mars 2014)

Programme de la journée du pôle Math-STIC

Axe 1 : Optimisation et apprentissage appliqués aux contenus numériques
Journée « Images et Signaux »
18 mars 2014
Amphi Fermat, Institut Galilée, Université Paris 13

 

  • 09:15-09:30          Accueil
  • 09:30-10:15          Frédéric Dufaux, Telecom ParisTech
    • Vidéo 3D - état de l'art, challenges et perspectives
  • 10:15-11:00          Philippe Guillottel, Technicolor
    • “Epitomes”: a new tool for image processing – application to video coding and super-resolution
  • 11:00-11:15          Pause
  • 11:15-12: 00         Lucas Letocart, LIPN - Université Paris 13 - SPC
    • Réduction de graphes pour la segmentation d'images
  • 12:00-13:30          Déjeuner - Buffet
  • 13:30-14:15          Laurent Duval, IFP
    • Filtrage adaptatif dans des trames d'ondelettes, application à la suppression d'échos en sismique
  • 14:15-15:00          Emilie Chouzenoux, IGM, Université de Paris-Est Marne-la-Vallée
    • Algorithme Explicite-Implicite pré conditionné. Application à la résolution de problèmes inverses de grande taille.
  • 15:00-15:15          Pause
  • 15:15-16:00          Hugues Talbot, A2SI, ESIEE
    • Filtrage de structures tibulaires
  • 16:00-16:45          Laurent Oudre, L2TI – Université Paris 13 - SPC
    • NMF et Online NMF : Méthodes, algorithmes et applications

Organisateurs
Azeddine BEGHDADI (L2TI)
Bassarab MATEI (LAGA)

Journée Optimisation et Réseaux (12 Juillet 2013)

Chers collègues,

Le pôle MathStic de l'université Paris 13 organise une journée "Optimisation, Réseaux et Apprentissage" le 12 juillet 2013
La journée aura lieu en amphi Euler, Institut Galilée, Université Paris 13.

Programme préliminaire de la journée :

09h00     Accueil
09h15     Achieving load proportional energy consumption in communication networks through adaptive network dimensioning (Antonio Capone - DEI, Politecnico di Milano)
10h00     Column Generation for multi-rate WMNs with continuous power control (Hervé Rivano - INRIA)
10h45     Pause
11h15     Maximizing throughput in telecommunication networks using multicast and network coding (Eric Gourdin - Orange)
12h00     Designing Content Centric Networks: optimal routing, bandwidth allocation and content placement (Fabio Martignon - LRI, Université Paris-Sud)
12h45     Buffet
14h00     Algorithms for the distributed control : spanning trees with constraints (Franck Butelle - LIPN, Université Paris 13)
14h30     On the deployment and dimensionning of WMN (Nadjib Achir - L2TI, Université Paris 13/INRIA)
15h00     Pause
15h30     The bounded cycle cover problem (Roberto Wolfler Calvo - LIPN, Université Paris 13)
16h00     Game theoric routing strategies in ITS,  (Naima Belakbir - pôle MathStic, Université Paris 13)

Pour des raisons d'organisation, merci de prévenir par mail les organisateurs si vous souhaitez venir (mais on ne refusera personne) :
-Roberto Wolfer Calvo : This email address is being protected from spambots. You need JavaScript enabled to view it.
-Khaled Boussetta : This email address is being protected from spambots. You need JavaScript enabled to view it.