he European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) took place in Athens, Greece from September 5th to 9th, 2011. This event builds upon a very successful series of 21 ECML and 14 PKDD conferences, which have been jointly organized for the past ten years.

It has become the major European scientific event in these fields and in 2011 it comprised presentations of contributed papers and invited speakers, a wide program of workshops and tutorials, a discovery challenge, a demo track and an industrial track.

The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2011) took place in Athens, Greece, during September 5-9, 2011. This year we have completed the first decade since the junction between the European Conference on Machine Learning and the Principles and Practice of Knowledge Discovery in Data Bases conferences, which as independent conferences date back to 1986 and 1997, respectively. During this decade there has been an increasing integration of the two fields, as ref lected by the rising number of submissions of top-quality research results. In 2008 a single ECML PKDD Steering Committee was established, which gathered senior members of both communities

General co-Chairs

  • Prof. A. Likas (Univ. of Ioannina, Greece)
  • Prof. Y. Theodoridis (Univ. of Piraeus, Greece)

Programme Commitee chairs

  • Prof. D. Gunopulos (Univ. of Athens, Greece)
  • Dr. T. Hofmann (Google Research)
  • Prof. Donato Malerba (Univ. of Bari, Italy)
  • Prof. M. Vazirgiannis (Athens Univ. of Economics and Business, Greece)

 

The 27th Conference on Uncertainty in Artificial Intelligence (UAI 2011) will be located in Barcelona, Spain, on July 14-17, 2011. Sessions will be held at the Campus Roger de Lluria of the Universitat Pompeu Fabra (UPF). The conference will happen just before the International Joint Conference on Artificial Intelligence (IJCAI).

UAI is the premier conference on issues relating to representation and management of uncertainty within the field of Artificial Intelligence. UAI is supported by the Association for Uncertainty in Artificial Intelligence (AUAI).

On July 14, before the main conference, we will have the 8th Bayesian Modelling Applications Workshop, a forum for interchange among those interested in real world applications of graphical models and Bayesian networks. A paper submitted to UAI2011 can also be submitted to the workshop. Accepted UAI application papers will be invited to an additional poster presentation at the Workshop, while papers that are not accepted for UAI will be refereed independently for the Workshop by the Workshop Program Committee.

UAI 2011 Organizing Committee

General chair Peter Grünwald CWI and Leiden University
Programm co-chairs Avi Pfeffer Charles River Analytics
Fabio G. Cozman Universidade de Sao Paulo
Local arrangements chair Lluis Godo Artificial Intelligence Research Institute (IIIA - CSIC)
Local arrangements Tommaso Flaminio, Enrico Marchioni Artificial Intelligence Research Institute (IIIA - CSIC)

Original contributions are sought regarding the development of theory, techniques, and applications of AI in BioMedicine, including the exploitation of AI approaches to medical informatics, healthcare organizational aspects, and to molecular medicine.
Contributions to theory may include presentation or analysis of the properties of novel AI methodologies potentially useful to solve medical problems.
Papers on techniques and methodologies should describe the development or the extension of AI methods and their implementation, and discuss the assumptions and limitations of the proposed methods and their novelty with respect to the state of the art.
Papers addressing systems should describe the requirements, design and implementation of new AI-inspired tools and systems, and discuss their applicability in the medical field.
Application papers should describe the implementation of AI systems to solve significant medical problems, and should present sufficient information to allow evaluation of the practical benefits of the system.

The scope of the conference includes the following areas:

  • Knowledge Acquisition and Management
  • Machine Learning, Knowledge Discovery and Data Mining
  • Biomedical Ontologies and Terminologies
  • Decision Support Systems
  • Neural Networks and Belief Networks
  • Reasoning under Uncertainty
  • Temporal and Spatial Representation and Reasoning
  • Case-Based Reasoning
  • Planning and Scheduling
  • Protocols and Guidelines
  • Information Retrieval
  • Natural Language Generation and Understanding
  • Biomedical Computer Vision, Imaging, and Signal Interpretation
  • Intelligent Agents
  • Telemedicine and Cooperative Systems
  • Cognitive Modeling
  • Healthcare Process Management

Program committee

  • Raza Abidi, Canada
  • Ameen Abu-Hanna, The Netherlands (Applications Session Co-chair)
  • Klaus-Peter Adlassnig, Austria
  • Steen Andreassen, Denmark (Applications Session Co-chair)
  • Pedro Barahona, Portugal
  • Riccardo Bellazzi, Italy
  • Petr Berka, Czech Republic
  • Isabelle Bichindaritz, USA
  • Elizabeth Borycki, Canada
  • Aziz Boxwala, USA
  • Paul de Clercq, The Netherlands
  • Carlo Combi, Italy (Doctoral Consortium Chair)
  • Michel Dojat, France
  • Henrik Eriksson, Sweden
  • Catherine Garbay, France
  • Adela Grando, UK
  • Femida Gwadry-Sridhar, Canada
  • Peter Haddawy, Macau
  • Arie Hasman, The Netherlands
  • Reinhold Haux, Germany
  • John Holmes, USA
  • Werner Horn, Austria
  • Jim Hunter, UK
  • Hidde de Jong, France
  • Elpida Keravnou, Cyprus
  • Pedro Larranaga, Spain
  • Nada Lavrac, Slovenia (Local Chair)
  • Johan van der Lei, The Netherlands
  • Xiaohui Liu, UK
  • Peter Lucas, The Netherlands
  • Roque Marin, Spain
  • Michael Marschollek, Germany
  • Carolyn McGregor, Canada
  • Paola Mello, Italy
  • Gloria Menegaz, Italy
  • Silvia Miksch, Austria
  • Stefania Montani, Italy
  • Mark Musen, USA
  • Barbara Oliboni, Italy
  • Niels Peek, The Netherlands
  • Mor Peleg, Israel (Scientific Chair)
  • Christian Popow, Austria
  • Silvana Quaglini, Italy
  • Marco Ramoni, USA
  • Alan Rector, UK
  • Stephen Rees, Denmark
  • Daniel Rubin, USA
  • Lucia Sacchi, Italy
  • Rainer Schmidt, Germany
  • Brigitte Seroussi, France
  • Yuval Shahar, Israel
  • Basilio Sierra, Spain
  • Costas Spyropoulos, Greece
  • Mario Stefanelli, Italy
  • Paolo Terenziani, Italy
  • Samson Tu, USA
  • Allan Tucker, UK
  • Frans Voorbraak, The Netherlands
  • Dongwen Wang, USA
  • Blaz Zupan, Slovenia
  • Pierre Zweigenbaum, France

Local Chair

Local Organization Committee

  • Tina Anzic
  • Damjan Demsar
  • Miha Grcar
  • Matjaz Jursic
  • Petra Kralj Novak
  • Dragana Miljkovic
  • Vid Podpecan
  • Borut Sluban

The International Conference on Machine Learning (ICML) is the premier conference for machine learning research. It is organized by the International Machine Learning Society (IMLS).

ICML
ICML

The fourteenth international conference on Artificial Intelligence and Statistics (AISTATS 2011) will be held in Ft. Lauderdale, FL, USA.  AISTATS is an interdisciplinary gathering of researchers at the intersection of computer science, artificial intelligence, machine learning, statistics, and related areas.  Since its inception in 1985, the primary goal of AISTATS has been to broaden research in these fields by promoting the exchange of ideas among them.  We encourage the submission of all papers which are in keeping with this objective.

Program Chairs

  • Geoff Gordon, Machine Learning Department, Carnegie Mellon University
  • David Dunson, Department of Statistical Science, Duke University

The Twenty-fourth Annual Conference on Neural Information Processing Systems (NIPS) is a single-track machine learning and computational neuroscience conference that includes invited talks, demonstrations and oral and poster presentations of refereed papers.

NIPS 2010
NIPS 2010

Intelligent machines

Can machines think? This has been a conundrum for philosophers for years, but the answer to this question also has real social importance. Modern robots can assist us in our homes and have human-like qualities. The internet provides us with personalized tools that learn from our behavior. It is therefore of more than academic importance that we learn about the actual cognitive powers of computers, and what we can expect of them in the future.On November 17, SNN organizes a one-day symposium in Nijmegen, entitled "Intelligent Machines". During the day, invited research leaders in the field of machine learning and robotics will present examples of intelligence in computers and will discuss their views for the future.

In addition, posters will provide a comprehensive overview of the research activities on machine learning in the Netherlands. Based on our experience with similar events in the past, we expect approximately 40 poster presentations. There is also an opportunity for companies to present their research and products.

The purpose of this meeting is to provide a platform for discussion and interaction between the academic and industrial research and development communities in the Netherlands.

For whom?

The symposium is designed to address a broad audience. The plenary talks aim at anyone who is interested in how intelligent computers may affect our society, now and in the future. The poster sessions present more technical results and aim provide concrete examples of how machine learning research is used in numerous applications.

What is machine learning?

Machine learning is a scientific discipline that is concerned with the design and development of algorithms that allow computers to learn behaviors based on empirical data, such as from sensor data or databases. A major focus of machine learning research is to automatically learn to recognize complex patterns and make intelligent decisions based on data; the difficulty lies in the fact that the set of all possible behaviors given all possible inputs is too complex to describe generally in programming languages, so that in effect programs must automatically describe programs. Machine learning methods are at the basis of many applications, ranging from vision to language processing, forecasting, pattern recognition, games, data mining, expert systems and robotics. The modern field of machine learning integrates many distinct approaches such as probability theory, logic, combinatoric optimization, search, statistics, reinforcement learning and control theory.

The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) was held in Casa Convalescència, Barcelona, Catalonia, Spain from September 20th to 24th, 2010 .

ECML 2010
ECML 2010