András Lörincz short bio: professor, senior researcher has been teaching at the Faculty of Informatics at Eötvös University, Budapest since 1998. His research focuses on distributed intelligent systems and their applications in neurobiological and cognitive modeling, as well as medicine. He has founded the Neural Information Processing Group of Eötvös University and he directs a multidisciplinary team of mathematicians, programmers, computer scientists and physicists. He has acted as the PI of several successful international projects in collaboration with Panasonic, Honda Future Technology Research and the Information Directorate of the US Air Force in the fields of hardware-software co-synthesis, image processing and human-computer collaboration. He authored about 200 peer reviewed scientific publications. He has received the Széchenyi Professor Award, Master Professor Award and the Széchenyi István Award in 2000, 2001, and 2004, respectively. In 20

04, he was awarded the Kalmár Prize of the John von Neumann Computer Society of Hungary. He has become an elected Fellow of the European Coordinating Committee for Artificial Intelligence for his pioneering work in the field of artificial intelligence in 2006.

Abstract: In recent years, a number of novel applications have emerged through „L1 Magic“, the intriguing property that cost functions using l0 norm (i.e., the minimization of the number of the elements of a basis set representing a given input) and cost functions using l1 norm are equivalent under certain conditions. This feature turns relevant NP-hard-looking problems to polynomial ones. Based on this and related recent advances in signal processing, we study a novel model in which signal is decomposed into a dense signal of low intrinsic dimension and into a sparse signal. In contrast to other approaches, this preprocessing in conjunction with efficient sparse coding can achieve structural sparseness thus allowing for the formation of highly overcomplete and highly sparse, but combinatorial dictionaries. We shall present some results for natural images and will discuss the advantages of the separation of the two types of representations for other data, including movies and texts.

A key requirement in packet switching networks is an efficient way to access information stored within the routers. The most obvious example is the routing table and its associated forwarding information, accessed at least once for each packet traversing the router, but advanced protocols may require to store and access flow state information too, adding scalability problems as well. In this seminar, an innovative, highly efficient way to exploit the cooperation between end nodes and intermediate systems will be presented. It is based on Distributed Linked Data Structures (DLDS), an extension of the classical linked data structures where pointers are stored in data packets, travel along the route from sender to receiver and address memory locations within the routers belonging to the path. When integrated in network protocols (for example as a new IP option field), DLDS provide the router the memory addresses needed to access the required information without the need of searching. This leads to constant cost procedures, increasing performance and overcoming scalability problems. DLDS may support several different applications; two of them will be discussed in detail: resource reservation for deterministic Quality of Service support (based on an algorithm called REBOOK) and routing tables lookup.

Pier Luca Montessoro was born in Torino, Italy, on November 25, 1961. He received the Dr. Eng. degree cum laude in Electronic Engineering from the Politecnico di Torino, Italy, in 1986. He has been with the Consiglio Nazionale delle Ricerche (C.N.R.), the Italian National Council for Scientific Research, from 1988 to 1992. During this period he has also been scientific consultant for the Digital Equipment Corporation (later Compaq) in Hudson, Mass. (USA) in the field of simulation for VLSI design. His teaching and research activities began at Politecnico di Torino where he taught computer programming, computer architectures, computer networks and databases in a Management Engineering course from 1990 to 1994. In November 1992 he moved to University of Udine as associate professor in computer science and since Novembre 2002 he is full professor. His teaching activity at the engineering faculty is on computer science fundamentals and computer networks. He recorded two video-courses for the Nettuno on-line university, he is author of several didactic publications, more than sixty scientific papers, some patents and together with Silvano Gai and Pietro Nicoletti wrote a popular book („Reti locali: dal cablaggio all’internetworking“, SSGRR, in italian) on structured cabling systems, LAN and internetworking, also included in their multimedia CD-ROM. His research interests, after several years spent on CAD for digital circuits design and, later, on multimedia systems for teleteaching and e-learning, are currently focused on computer networks and network security and on pervasive computing. From 2003 to 2009 Pier Luca Montessoro has been head of the Electrical, Management and Mechanical Engineering Department and from 1995 to 2002 director of the Computer Center of the University of Udine. He has been member of the NCGT of the CRUI („Conferenza dei Rettori delle Università Italiane“) for the GARR computer network, the italian research network, president of master course in Multimedia Sciences and Technologies of the University of Udine, rector’s delegate for the computer networks and telematic systems of the University of Udine, member of the Tecnical Board („Comitato Tecnico“) of the CINECA consortium; He is currently representative of University of Udine in several national committees. Related to the interest in multimedia systems, Pier Luca Montessoro developed some studies about musical piracy and has been consultant of magistrates in several proceedings. He is also member of SIAE („Società Italiana degli Autori ed Editori“), the italian authors and editors society, as composer and song writer.

In der Vortragsreihe des Projektes Informatik verstehen hat am 8. Juni Herr Prof. Böszörmenyi vom Institut für Informationstechnologie über das Thema „Die unsichtbaren Diener – Der Compiler und seine Artgenossen“ referiert. Neben Mitarbeitern der Universität nahmen erfreulicherweise auch Lehrer und zahlreiche Schüler am Vortrag teil.

Link zu den Vortragsfolien: http://www.itec.uni-klu.ac.at/~laszlo/courses/cb/Compiler.pdf

Abstract:
Popular programming languages offer thousands of add-on libraries or modules. Popular applications offer thousands of add-on plug-in modules. We consider the problem of recommending a small set of related modules when someone visits a page describing a module. There are three promising sources of information for these recommendations. The first is textual similarity among the descriptions of modules. The second is co-mention of the modules in forum conversations. The third is co-installation of modules in public sites that report on which modules are used. I will report on a deployment on drupal.org, comparing the effectiveness (in terms of user click-throughs) of recommenders that use the three sources. I will also describe a further experiment, about to be released on drupal.org, that dynamically updates the recommendations based on users‘ click behaviors, using a Multi-Armed Bandit learning algorithm. I will describe how we are using the three sources of information to set „priors“ for the bandit algorithm, and how we will assess the amount of improvement in recommendations from using the

priors as compared to a prior-free version of the bandit algorithm.
Background paper: http://portal.acm.org/citation.cfm?id=1639714.1639737

Paul Resnick is a Professor at the University of Michigan School of Information. He previously worked as a researcher at AT&T Labs and AT&T Bell Labs, and as an Assistant Professor at the MIT Sloan School of Management. He received the master’s and Ph.D. degrees in Electrical Engineering and Computer Science from MIT, and a bachelor’s degree in mathematics from the University of Michigan.
Professor Resnick’s research focuses on SocioTechnical Capital, productive social relations that are enabled by the ongoing use of information and communication technology. His current projects include analyzing and designing reputation systems, ride share coordination services, and applying principles from economics and social psychology to the design of on-line communities.
Resnick was a pioneer in the field of recommender systems (sometimes called collaborative filtering or social filtering). Recommender systems guide people to interesting materials based on recommendations from other people. His articles have appeared in Scientific American, Wired, Communications of the ACM, The American Economic Review, Management Science, and many other publications.

Mit der Entwicklung der Informationstheorie gelang C. E. Shannon bereits im Jahre 1948 der Beweis, das mittels geeigneter Codierverfahren auch über gestörte Übertragungskanäle prinzipiell eine fehlerfreie digitale Übertragung möglich ist, solange nicht versucht wird, mehr Daten zu übertragen als die Kapazität des Kanals zulässt. Dieses Kanalcodierungstheorem leitete eine breite Forschungstätigkeit auf dem Gebiet der Kanalcodierung ein. Dennoch wurden über viele Jahre trotz des Einsatzes anspruchsvollster mathematischer Methoden nur eher bescheidene Fortschritte erreicht und das Ziel, die informationstheoretische Kapazität von Übertragungskanälen in der Praxis nutzbar zu machen, erschien grundsätzlich  unerreichbar. Erst durch die Zufallserfindung der sog. „Turbo-Codes

Abstract: Visual information retrieval (VIR) is an active and vibrant research area which attempts at providing means for organizing, indexing, annotating, and retrieving visual information (images and videos) form large, unstructured repositories.  In its early years (1995-2000) the research efforts were dominated by content-based approaches contributed primarily by the image and video processing community.  Later, it was widely recognized that the challenges imposed by the semantic gap (the lack of coincidence between an image’s visual contents and its semantic interpretation) required a clever use of textual metadata (in addition to information extracted from the image’s pixel contents) to make image and video retrieval solutions efficient and effective. The need to bridge (or at least narrow) the semantic gap has been one of the driving forces behind current VIR research. Additionally, other related research problems and market opportunities have started to emerge, offering a broad range of exciting problems for computer scientists and engineers to work on.

This talk revisits the field of content-based image retrieval (CBIR) 10 years after „the end of the early years“ (as announced in a seminal paper in the field) and highlights the most relevant advances, pending challenges, and promising opportunities in CBIR and related areas. Particularly, it includes an overview of  the important field of medical image retrieval, its main challenges and opportunities.

Dr. Oge Marques is an Assoc

iate Professor and Associate Chairman in the Department of Computer Science and Engineering at Florida Atlantic University in Boca Raton, Florida. He received his Ph.D. in Computer Engineering from Florida Atlantic University in 2001, his Masters in Electronics Engineering from Philips International Institute (Eindhoven, NL) in 1989 and his Bachelor’s Degree in Electrical Engineering from UTFPR (Curitiba, Brazil), where he also taught for more than 10 years before moving to the USA.

His research interests include: image processing, analysis, annotation, search, and retrieval; human and computer vision; and video processing and analysis. He has more than 20 years of teaching and research experience in the fields of image processing and computer vision, in different countries (USA, Austria, Brazil, Netherlands, Spain, France, and India) and capacities. He is the (co-) author of 4 (four) books in these topics, including the forthcoming textbook “Practical Image and Video Processing Using MATLAB” (Wiley, 2011). He has also published several book chapters and more than 50 refereed journal and conference papers in these fields. He serves as a reviewer and Editorial Board member for several leading journals in computer science and engineering. He is a senior member of the ACM, senior member of the IEEE, and a member of the IEEE Computer Society, IEEE Education Society, and the honor societies of Tau Beta Pi, Sigma Xi, Phi Kappa Phi and Upsilon Pi Epsilon. 

Abstract: The energy sector will undergo fundamental changes over the next ten years. Prices for fossil energy resources are continuously increasing, there is an urgent need to reduce CO2 emissions, and the United States and European Union are strongly motivated to become more independent from foreign energy imports. These factors will lead to installation of large numbers of distributed renewable energy generators, which are often intermittent in nature.

This trend conflicts with the current power grid control infrastructure and strategies, where a few centralized control centers manage a limited number of large power plants such that their output meets the energy demands in real time. As the proportion of distributed and intermittent power production capacity increases, this task becomes much harder, especially as the local and regional distribution grids where renewable energy producers are usually installed are currently virtually unmanaged, lack real time metering and in many cases are not built to cope with power flow inversions.

While the hierarchical command-and-control approach served well in a world with a few large scale generation facilities and many small consumers, a more flexible, decentralized, and self-organizing control infrastructure will have to be developed that can be actively managed to balance both the large grid as a whole, as well as the many lower voltage sub-grids. One strong candidate for this control infrastructure is to create energy markets at the retail level. To help mitigate the risk of instituting such markets in the real world, we are deve

loping a competitive market simulation testbed. We expect that this testbed will stimulate research and development of market structures along with automated software agents that can support decision making in these markets. Participants in the competition will design intelligent agents that will act as brokers, building portfolios of energy producers and consumers, and matching energy supply from producers with energy demand from consumers. The competition will closely model reality by bootstrapping the simulation environment with real historic load, generation, and weather data.

Wolfgang Ketter is Assistant Professor at the Department of Decision and Information Sciences at the Rotterdam School of Management of the Erasmus University. He received his Ph.D. in Computer Science from the University of Minnesota in 2007. He founded and runs the Learning Agents Research Group at Erasmus (LARGE). The primary objective of LARGE is to research, develop, and apply autonomous and mixed-initiative intelligent agent systems to support human decision making in the area of business networks, electronic markets, information systems and supply-chain management. He was co-chairing the TADA workshop at AAAI 2008, the general chair of TAC 2009, and is member of the board of directors of the association for trading agent research since 2009. He is the program co-chair of the International Conference of Electronic Commerce 2011. His research has been published in various information systems, and computer science journals such as AI Magazine, Decision Support Systems, Electronic Commerce Research and Applications, European Journal of Information Systems, INFORMS OR/MS Today, and International Journal of Electronic Commerce. He serves on the editorial board of Electronic Commerce Research and Applications.