Pro-Multidis-CM


PROcesamiento MULTImedia DIStribuido
Programa S - 0505/TIC/0233, IV PRICIT, CM

Procesamiento Multimedia Distribuido

PRO-MULTIDIS es un programa de investigación financiado por la Comunidad de Madrid (CM) en el marco del Plan Regional de Investigación Científica e Innovación Tecnológica (PRICIT) y que integra a cinco grupos de reconocido prestigio de cuatro universidades madrileñas. Apoyándose en la existencia de amplios conocimientos comunes y en la complementariedad de importantes experiencias específicas, se propone desarrollar nuevos procedimientos para telecomunicaciones avanzadas mediante la utilización de inteligencia para codificación multimedia y diseño y gestión de redes ad hoc, además de generar subproductos aprovechables en otros ámbitos de las Tecnologías de la Información y las Comunicaciones (TIC). Programa de Actividades

La duración prevista del Programa es de cuatro años a partir de enero de 2006. Durante este periodo, la actividad técnica de los participantes se estructurará entorno a las siguientes líneas de trabajo:

  • L1: Crear, desarrollar, analizar y evaluar nuevos métodos máquina por superposición de modelos en arquitecturas convencionales, y derivar posibles versiones adaptativas.
  • L2: Diseñar, aplicar y analizar nuevos métodos de extracción de información a partir de nodos sensores distribuidos (tanto físicos como virtuales) considerando los problemas de captación, fusión y comunicación.
  • L3: Analizar, extraer, describir, indexar, adaptar, codificar y transmitir contenidos audiovisuales y multimedia, operando sobre información de varias calidades (incluyendo televisión digital y de alta definición) y estructuras 3D.
  • L4: Desarrollar nuevas tecnologías para optimización de redes de comunicaciones inalámbricas, permitiendo su despliegue ubicuo con banda ancha, bajo consumo, alta tolerancia a fallos en nodos, y garantizando variadas Calidades de Servicio.

Palabras Clave: aprendizaje máquina; modelado; adaptatividad; fusión; detección distribuida; codificación fuente-canal; procesamiento distribuido; televisión digital; visión artificial; realidad aumentada; redes de sensores (inalámbricas); computación ubicua; redes malladas; diversidad.

USER-CENTERED ISSUES IN RECOMMENDER SYSTEMS

Ponente: Dr. Nava TINTAREV (Telefónica I+D, Barcelona)

Recommender systems suggest items to purchase or examine based on users' preferences. In recent years there has have been a shift in what is considered important in recommender systems – from recommendation accuracy to other more user-centered criteria such as transparency, trust, satisfaction etc. In addition, traditional evaluation metrics such as root mean square error (RMSE) are increasingly being questioned.
In this talk, the speaker will give an overview of recommender systems, as well as related user-centered issues. Topics will include the speaker’s doctoral work on evaluations and explanations in recommender systems, and work currently being conducted at Telefónica R&D such as personalization for a travel scenario (within the scope of the WeKnowIt European project), as well as work with colleagues (X. Amatriain, J.M. Pujol, and N. Oliver) on how natural noise or inconsistency in user ratings affects errors in recommendation accuracy.

Fecha: 6 de Noviembre de 2009
Horario: 12:30 pm
Lugar: EPS Universidad Carlos III de Madrid, Campus de Leganés. Aula 4.3.A05, Edificio Torres Quevedo

Toward Cognitive Coexistence of Heterogeneous Wireless Users

Ponente: Prof. Lang TONG (SEE, Cornell University, Ithaca, NY, USA)

The explosive growth of wireless communications has presented us an intriguing spectrum paradox: On the one hand, the overcrowding spectrum allocation threatens the potential deployment of new wireless services. On the other hand, at a particular time and location, the spectrum is often only used sparsely, despite the presence of many potential unlicensed users. The root of this paradox, now widely recognized, is the static spectrum allocation and the rigid access policy that prevent a more efficient and dynamic usage of wireless channels.

We present in this talk some recent developments in opportunistic spectrum access using software-defined cognitive radios. We are interested in the coexistence of primary wireless users with cognitive secondary users capable of channel sensing and adaptive transmission. We focus on a decision-theoretic approach aimed at achieving an optimal tradeoff among opportunity learning, opportunity exploitation, and interference mitigation. We illustrate the proposed approaches in the context of the cognitive coexistence of Bluetooth/WLAN devices.

Fecha: 10 de Junio de 2009
Horario: 12:00
Lugar: EPS Universidad de Alcalá, Sala de Grados

Distributed Sensing and Inference in Random Information Fusion Networks

Ponente: Prof. Lang TONG (SEE, Cornell University, Ithaca, NY, USA)

Advances in microelectronics and wireless communication technology make it possible that a large number of sensors are networked to perform collaboratively tasks such as monitoring, learning, and computation. These sensors form a fusion network that allows sensors process their observations locally, share the information with other nodes, and extract information at fusion centers. The objective of an information fusion network is to extract useful information from these sensors in an efficient and economic fashion; there is a fundamental tradeoff between the cost of data fusion and the performance achieved at fusion centers.

This talk examines scalable fusion policies that achieve optimal inference at the fusion center and have a constant average cost per sensor as the size of the network increases. To this end, it is necessary to exploit statistical correlations among observations of sensor nodes. For statistical inference involving random dependency graphs, for example, we show that the sparsity of the dependency graph and that of the network graph play a crucial role of scalable information fusion. Some simple energy efficient fusion policies are presented.

Fecha: 09 de Junio de 2009
Horario: 10:00 - 11:00
Lugar: EPS Campus de Fuenlabrada de la Universidad Rey Juan Carlos, Edificio Departamental, Salón de Grados

Third Generation Machine Intelligence

Ponente: Prof. Christopher M. BISHOP (Ass. Director, Microsoft Research, Cambridge, UK)

The first successful applications of machine intelligence were based on expert systems constructed using rules elicited from human experts. Limitations in the applicability of this approach helped drive the second generation of machine intelligence methods, as typified by neural networks, which can be characterised as black box statistical models fitted to large data sets. In this talk I will describe a new paradigm for machine intelligence which has emerged over the last five years, and which allows strong prior knowledge from domain experts to be combined with machine learning techniques to enable a new generation of large-scale applications. The talk will be illustrated with example case studies.

Fecha: 25 de Mayo de 2009
Horario: 18:00
Lugar: EPS Universidad Carlos III, Edificio Padre Soler.

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