Machine Learning List: Vol. 18, No. 1
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Machine Learning List: Vol. 18, No. 1
by Pat Langley
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Machine Learning List: Volume 18, Number 1 Wenesday, January 18, 2006 ************************************************************************ Contents Calls for Papers & Participation Pattern recognition competition Symposium on Adaptation and Learning on the Web Sixth SIAM Data Mining Conference - Workshops and Tutorials COLT 2006 AAAI-06 workshop on Learning for Search January 18 paper submission deadline for GECCO-2006 conference Intelligent User Interfaces 2006 ALAMAS 2006 CEAS 2006 International Workshop on Feature Selection for Data Mining Workshop on Hierarchical Autonomous Agents/Multi-Agent Systems OBUPM-2006 Workshop at GECCO 2006 Book Chapters on Hybrid Evolutionary Systems Tackling Computer Systems Problems with Machine Learning ICGI 2006 Tenjinno Machine Translation Competition ICML 2006 Call for Workshops/Tutorials and Papers CogSci 2006 ICCL Summer School on Knowledge Structures ECAI2006 Workshop Abduction and Induction New Journal---ACM Transactions on Knowledge Discovery from Data MedGEC - GECCO Workshop on Medical Applications of Genetic and Evolutionary Computation ISMIS 2006 ECML-2006/PKDD-2006 Reminders EvoOpt 2006 S+SSPR 2006 MBR06_China UK KDD Symposium (UKKDD'06) Systems Announcements The Alchemy system for statistical relational AI Career Opportunities Two open PhD positions in machine learning at IDIAP Postdoc positions at Oregon State University Ph.D. program in Cognitive Science at RPI Computer Science faculty position at U of Vermont Software engineer position at the University of Washington Postdoctoral position in computational biology/bioinformatics Open research fellowship in object recognition and medical imaging Bioinformatics postdoc at Princeton ************************************************************************ The Machine Learning List is moderated. Contributions should be relevant to the scientific study of machine learning. Please send submissions for distribution to: ml@.... For requests to be added, removed, or to change your email address, send email to: ml-request@.... To keep mailings to a manageable size, please keep submissions brief. For meeting announcements, do highlight the meeting Web site and the goals of the event but omit information such as the program committee and talk schedules. Also, only first calls for papers/participation and brief change of deadline announcements will be included. The ML List moderator reserves the right to omit/edit submissions to meet these criteria. ************************************************************************ Date: Mon, 10 Oct 2005 10:13:57 +0200 From: Isabelle Guyon <isabelle@...> To: ml@... Subject: Pattern recognition competition Dear colleagues, We are organizing a competition entitled Performance Prediction Challenge that is described at: http://www.modelselect.inf.ethz.ch/ How well can you predict how good you are? Find out: compete to accurately predict your generalization performance. This problem, which has great practical importance (e.g., in pilot studies), poses theoretical and computational challenges. Is cross-validation the best solution? How many folds should one use? Can theoretical performance bounds help assess generalization? You will have opportunities to publish at WCCI 2006 (Vancouver, July 2006) and in a special issue of JMLR. Check the web site! ------------------------------------------------------------------------ Date: Wed, 16 Nov 2005 13:04:25 +0000 From: Simon Price <simon.price@...> To: undisclosed-recipients Subject: Symposium on Adaptation and Learning on the Web CALL FOR PAPERS Symposium on Adaptation and Learning on the Web 3rd to 4th April 2006 University of Bristol, Bristol, UK http://aisb.ilrt.org This symposium will explore whether learning and Semantic Web technologies might be usefully combined with ideas from biological systems so that a future Web would be able to automatically adapt to new situations and be as flexible as possible. To achieve this the symposium aims to bring together researchers, from disciplines such as machine learning, data mining, information extraction, computational linguistics, statistics and biologically inspired backgrounds, who share a common interest in how adaptation and learning, in various forms, may be used in a future Web, Semantic Web, GRID and Web Services. The symposium will take place as part of AISB'06: Adaptation in Artificial and Biological Systems, held at University of Bristol, Bristol, UK, April 3rd-6th 2006. SUBMISSIONS Research spanning the numerous fields that make up the intersection between AI and the Web is, by its very nature, highly multidisciplinary. This symposium will offer a chance for currently disjointed communities to begin to develop a common vocabulary - the first step towards sharing ideas and disseminating work across subject boundaries. Topics of interest include but are not limited to: * Semantic Web, Semantic Grid and Web Services * Biologically inspired systems * Ontology learning, extraction and evolution * Semantic integration, co-ordination and matching * Artificial immumity on the Web * Personalisation and profiling on the Web * Adaptive search and information retrieval * Desktop search and the Personal Semantic Web * Augmented memory, user interest and focus * Security, trust and privacy * Social network mining * Collabative filtering, annotation and extraction * Recommender systems We also encourage submissions which relate results from other areas (e.g., data mining, information retrieval, knowledge representation, computational linguistics, inductive logic programming) to the symposium topics. Papers should be submitted as PDF files to simon.price@.... Formatting instructions are available at the symposium website. IMPORTANT DATES Submission of papers by: 3rd February 2006 Notification of decision: 27th February 2006 Camera ready copies by: 13th March 2006 ------------------------------------------------------------------------ Date: Sun, 20 Nov 2005 18:57:14 -0600 From: Ian Davidson <davidson@...> To: ml@... Subject: Sixth SIAM Data Mining Conference - Workshops and Tutorials The SIAM Data Mining (SDM) organizing committee is pleased to present the following workshops and tutorials that will be held in conjunction with SDM'06 in the Washington DC Area (Bethesda, Maryland), USA: Workshop on Feature Selection for Data Mining Workshop on Text Mining Workshop on High Performance and Distributed Mining Workshop on Spatial Data Mining: Consolidation and Renewed Bearing Workshop on Link Discovery Workshop on Biomedical Informatics Workshop on Scientific Data Mining Details on these workshops, including calls for papers, submission deadlines (typically between Jan 7th and 10th for all workshops), organizing committees and other information, can be found at: http://www.siam.org/meetings/sdm06/workshops.htm Tutorials 1. Randomized Algorithms for Matrices and Massive Data Sets Petros Drineas (RPI) and Michael W. Mahoney (Yale) 2. From Unsupervised to Semi-supervised Learning Dimitrios Gunopulos (UCR), Michalis Vazirgiannis (Athens U. of Economics), and Maria Halkidi (Athens U. of Economics) Details on these tutorials can be found at: www.siam.org/meetings/sdm06/tutorials.htm ------------------------------------------------------------------------ Date: Thu, 24 Nov 2005 16:18:20 +0100 From: Hans Ulrich Simon <simon@...> To: ml@... Subject: COLT 2006 CALL FOR PAPERS The 19th Annual Conference on Learning Theory Carnegie Mellon University, Pittsburgh, Pennsylvania June 22 - 25, 2006 http://learningtheory.org/colt2006 (In co-location with ICML 2006) The 19th Annual COLT (Conference on Learning Theory) will be held in Pittsburgh, PA, USA, June 22-25, 2006. We invite submissions of papers addressing the theoretical modeling and analysis of all aspects of learning and empirical inference. We strongly support a broad definition of learning theory, including: * Analysis of learning algorithms and their generalization ability * Computational complexity of learning * Bayesian analysis * Statistical mechanics of learning systems * Optimization procedures for learning * Inductive inference * Boolean function learning * Inductive logic programming * Unsupervised and semi-supervised learning * On-line learning and relative loss bounds * Learning in planning and control (including reinforcement learning) * Mathematical analysis of learning in related fields We welcome theoretical papers about learning that do not fit into the above categories. We are particularly interested in papers that include viewpoints new to the COLT community. While the primary focus of the conference is theoretical, papers can be strengthened by the inclusion of relevant experimental results. We also welcome experimental and algorithmic papers provided they are relevant to the focus of the conference by elucidating theoretical results in learning. PAPER FORMAT: see http://www.springer.de/comp/lncs/authors.html OPEN PROBLEMS SESSION: We also invite submission of open problems (see separate call). These should be constrained to two pages using the same formatting as for the full papers. There is a shorter reviewing period for the open problems. Accepted contributions will be allocated short presentation slots in a special open problems session and will be allowed two pages each in the proceedings. Dates/deadlines: Electronic submission of papers January 21, 2006 Notification of acceptance or rejection March 10, 2006 Electronic submission of two-page open problems March 15, 2006 Final submission of all papers (incl. LaTex files) March 25, 2006 Conference dates June 22-25, 2006 Please note the CONFLICT between submissions to STOC 2006 (Notification: January 31) and submissions to COLT 2006 (Submission deadline: January 21). ------------------------------------------------------------------------ Date: Tue, 29 Nov 2005 10:41:08 PST From: Wheeler Ruml <ruml@...> To: ml@... Subject: AAAI-06 workshop on Learning for Search The AAAI-06 Workshop on Learning for Search http://www.cs.ubc.ca/~hutter/aaai06_ws Heuristic search is among the most widely used techniques in AI. In its different varieties, such as tree-based search and local search, it provides the core engine for applications as diverse as planning, parsing, and protein folding. One of the most promising avenues for developing improved search techniques is to use some kind of algorithmic component that learns from experience. Many disparate techniques have arisen in recent years that exploit learning to improve search and problem solving. These techniques can be off-line or on-line, based on hard constraints or probabilistic biases, and applied to tree-structured or local search. This workshop aims to bring together researchers and practitioners from the various subcommunities where such methods have arisen in order to learn from each other, develop common understandings, and inspire new algorithms and approaches. Relevant topics include, but are not limited to: * adaptive and self-tuning algorithms * automated parameter tuning * automated portfolio design * clause learning * computing search space features * decision-theoretic approaches to learning in search * dynamic portfolio design * exploiting models of search spaces * exploiting performance profiles or run-time distributions * incremental and active learning in search * learning to select operators or heuristic functions * metareasoning from experience * model-based search * reinforcement learning for search algorithms * runtime prediction * speed-up learning * uncertainty in runtime prediction There will also be a separate workshop at AAAI-06 on "Heuristic Search, Memory-based Heuristics and Their Applications", held on a separate day. Feel free to submit to both workshops. Potential participants should submit technical papers formatted in the AAAI conference style. Technical papers should be 6-8 pages in length. All submitted papers will be carefully peer-reviewed for quality and relevance. Other potential participants should submit a statement of relevant research interests, maximum 2 pages in length. All accepted submissions will appear in the workshop notes. The submission deadline is March 31, 2006. Submissions should be sent via email in PDF format to lfs06submissions@.... Per AAAI policy, participation in the workshop is by invitation only and all workshop participants must register for the main AAAI-06 conference. All interested in the workshop topic are invited to join the Yahoo group: http://groups.yahoo.com/group/learning_for_search/ ------------------------------------------------------------------------ Date: Tue, 06 Dec 2005 16:05:24 -0600 From: daveg@... Subject: January 18 paper submission deadline for GECCO-2006 conference To: gecco-announce@... CALL FOR PAPERS: 2006 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE July 8-12, 2006 (Saturday-Wednesday) Renaissance Seattle Hotel, Seattle, Washington, USA Largest Conference in the Field of Genetic and Evolutionary Computation PAPER SUBMISSION DEADLINE: Wednesday, February 1, 2006 Organized by ACM SIG-EVO (www.sigevo.org/GECCO-2006) 15th International Conference on Genetic Algorithms (ICGA) and the 11th Genetic Programming Conference (GP) The Genetic and Evolutionary Computation Conference (GECCO-2006) will present the latest high-quality results in the growing field of genetic and evolutionary computation. Topics include: genetic algorithms, genetic programming, evolution strategies, evolutionary programming, real-world applications, learning classifier systems and other genetics-based machine learning, evolvable hardware, artificial life, adaptive behavior, ant colony optimization, swarm intelligence, biological applications, evolutionary robotics, evolutionary combinatorial optimization, coevolution, artificial immune systems, and more. 16 Program Tracks One conference - Many mini-conferences Free Tutorials and Workshops Visit www.sigevo.org/GECCO-2006 for information about tutorials, workshops, papers submission and deadlines, paper review process, electronic submission procedures, formatting details, student travel grants, hotel reservations, travel discounts, student housing, graduate student workshop, late-breaking papers, etc. GECCO is sponsored by the Association for Computing Machinery (ACM) Special Interest Group of Genetic and Evolutionary Computation (SIGEVO). Contact ACM SIG services, 1515 Broadway, New York, NY l0036. Phone: 800-342-6626 in USA and Canada and 202-626-0500 international. ------------------------------------------------------------------------ Date: Fri, 9 Dec 2005 15:50:54 -0800 From: Tessa Lau <tessalau@...> To: papers@... Subject: Intelligent User Interfaces 2006 International Conference on Intelligent User Interfaces (IUI 2006) http://www.iuiconf.org/ Sydney, Australia 29 January to 1 February 2006 IUI 2006 is the principal international forum for the presentation and discussion of outstanding research and applications involving intelligent user interfaces, a field at the intersection of Human Computer Interaction and Artificial Intelligence. The conference highlights include invited talks by Hiroshi Ishiguro and Jeffrey Shaw, an exciting program including 30 technical presentations on all aspects of intelligent user interfaces, and a dinner cruise on Sydney Harbour. There will also be three tutorials and four workshops (on Jan 29): T1: Introduction to Human-Robot Interaction T2: Interfaces Everywhere - Interacting with the Pervasive Computer T3: Constructive Dialogue Management for Speech-based Interaction Systems WS1: Workshop on Cognitive Prostheses and Assisted Communication (CPAC) WS2: Multi-User and Ubiquitous User Interfaces (MU3I '06) WS3: Intelligent User Interfaces for Intelligence Analysis WS4: Effective Multimodal Dialogue Interfaces For more information and to register for the conference, see http://www.iuiconf.org The advance registration deadline is midnight 22 January (Sydney time). ------------------------------------------------------------------------ Date: Mon, 12 Dec 2005 10:43:08 +0100 From: Maarten Peeters <mjpeeter@...> To: ml@... Subject: ALAMAS 2006 Sixth European Symposium on Adaptive and Learning Agents and Multi-Agent Systems (ALAMAS 2006) http://como.vub.ac.be/alamas2006 Adaptive Learning Agents and Multi-Agent Systems is an emerging multi-disciplinary area encompassing computer science, software engineering, biology, as well as cognitive and social sciences. The goal of this symposium is to increase awareness and interest in adaptive agent research, encourage collaboration between ML experts and agent system experts, and give a representative overview of current research in the area of adaptive agents. The symposium will serve as an inclusive forum for the discussion on ongoing or completed work in both theoretical and practical issues. The symposium is the sixth in a series that have taken place annually since 2001. After these five successful symposia, ALAMAS will be held at the Vrije Universiteit Brussel on Monday the 3rd and Tuesday the 4th of April 2006. The organization is in the hands of the Computational Modeling Lab. The workshop topic is situated at the intersection of two areas, namely, Adaptation/Learning and Agents/Multi-Agent Systems. The workshop will focus on but is not necessarily limited to: Learning of Co-ordination Distributed Learning Game-Theoretical and Analytical Approaches Emergent Organisation/Behaviour Studies of Complexity in Multi-Agent Learning Systems Evolutionary Agents Evolution of Individual Learning in Multi-Agent Systems Logic-Based Learning Learning in Reactive Agents Adaptive Mobile Agents Software Engineering Techniques and Tools Biological inspired Multi-Agent Systems Industrial and Large Scale Applications of Learning Agents Submission deadline: January 30, 2006 Notification of acceptance: February 24, 2006 Deadline for camera-ready: March 24, 2006 Symposium: April 3 and 4, 2006 ------------------------------------------------------------------------ Date: Mon, 19 Dec 2005 07:52:47 -0800 From: Dave Crocker <dcrocker@...> To: ml@... Subject: CEAS 2006 Call for Papers THE THIRD CONFERENCE ON EMAIL AND ANTI-SPAM (CEAS 2006) Thursday July 27 and Friday July 28, 2006 Mountain View, California http://ceas.cc/2006/cfp.html The Conference on Email and Anti-Spam invites short and long paper submissions on research results pertaining to a broad range of issues in email and internet communication. Submissions may address issues relating to any form of electronic messaging, including traditional email, instant messaging, mobile telephone text messaging, and voice over IP. Issues of interest include the analysis and abatement of abuses (spam, phishing, identity theft, and privacy invasion) as well as enhancements to and novel applications of electronic messaging. Past proceedings are available on-line: 2004: http://ceas.cc/papers-2004/acceptedpapers.htm 2005: http://ceas.cc/2005/schedulepapers.htm Novel departures from previously included topics are welcome. SUGGESTED TOPICS: Message filtering, blocking, authentication; Message organization; Message retrieval; Systems and network issues; Evaluation; Analysis; User issues; Social issues; Legal issues: KEY DATES: Paper submission deadline: March 23, 2006 Notification of acceptance: May 22 Final camera-ready version of papers: June 22 Conference: July 27 and 28, 2006 Submissions must use the CEAS electronic system. The style for submissions and final papers is a two-column, 8.5 by 11 inch format, as specified in http://www.ceas.cc/2006/format.htm For more information, send email to information@... ------------------------------------------------------------------------ Date: Wed, 21 Dec 2005 13:37:38 -0500 (EST) From: Lei Yu <lyu@...> To: ml@... Subject: International Workshop on Feature Selection for Data Mining International Workshop on Feature Selection for Data Mining - Interfacing Machine Learning and Statistics in conjunction with 2006 SIAM Data Mining Conference April 22, 2006, Bethesda, Maryland http://enpub.eas.asu.edu/workshop/2006 Knowledge discovery and data mining (KDD) is a multidisciplinary effort to extract nuggets of information from data. Massive data sets have become common in many applications and pose novel challenges for KDD. Along with changes in size, the context of these data runs from the loose structure of text and images and to designs of microarray experiments. This workshop will bring together researchers from different disciplines and encourage collaborative research in feature selection. Feature selection is an essential step in successful data mining applications. Feature selection has practical significance in many areas such as statistics, pattern recognition, machine learning, and data mining. The objectives of feature selection include: building simpler and more comprehensible models, improving data mining performance, and helping to prepare, clean, and understand data. Submissions that consider knowledge in feature selection will receive special consideration. Knowledge here means some declarative knowledge that can be explicitly expressed by a domain expert such as constraints. We encourage presentations featuring both the theory behind feature selection as well as novel applications to data. Additional workshop topics include the following: Dimensionality reduction; Feature construction; Improving data mining performance; Novel data structures; Streaming data reduction and time series; Selection for labeled and unlabeled data; Modeling variable and feature selection; Goodness measures and evaluation; Ensemble methods; Selection bias; Sampling methods; Selection with small samples; Cross-discipline comparative studies; Integration with data mining algorithms; Real-world case studies and applications; Emerging challenges. Available at the workshop website: Paper Format, Important Dates, and Submission Submissions should be emailed to featureselection@... Quality short papers, position papers are also welcome. The deadline for submission: January 9, Monday. Acceptance notification: February 1, Wednesday Camera ready due: February, 14, Tuesday More information can be found at the workshop website http://enpub.eas.asu.edu/workshop/2006. ------------------------------------------------------------------------ Date: Thu, 22 Dec 2005 17:25:15 +0100 (MET) From: Edwin de Jong <dejong@...> To: ml@... Subject: Workshop on Hierarchical Autonomous Agents/Multi-Agent Systems H-AAMAS: Hierarchical Autonomous Agents and Multi-Agent Systems Half-day workshop at the AAMAS-06 conference May 9 (afternoon), 2006 http://www.science.uva.nl/~bram/HAAMAS/ Submissions must be sent to bram (at) science.uva.nl by 2/1/06. Notification of acceptance or rejection will be sent by 2/19/06. In a variety of fields related to autonomous agents and multi-agent systems, hierarchical approaches are beginning to emerge as one of the premier ways of dealing with the scale and complexity of interesting, real-world problems. These fields include reinforcement learning, evolutionary algorithms, multi-agent learning, mapping and planning in robotics, Markov processes, and networked sensor and information systems. The general strategy in all these methods is "to divide and conquer": a large, complex problem is decomposed (possibly recursively) into smaller, simpler subproblems. Hierarchical methods generally represent and solve tasks at multiple spatial and/or temporal resolutions, and higher levels or layers are in some sense abstractions of the details of lower levels. However, precise, formal relationships between hierarchical methods in different fields are virtually unknown, while presumably hierarchical methods in one field may profit greatly from advances made on hierarchical methods in another field. The purpose of this workshop is to bring together researchers from these different fields to discuss the similarities between the various hierarchical methods, inspire cross-fertilization, prevent superfluous reinventions of the same "hierarchical wheels", and identify important questions for further research on hierarchical methods. We invite papers on hierarchical methods, in particular related to the following, but not limited to the following issues: -Which mathematical frameworks can provide the solid theoretical underpinnings of hierarchical methods? -How can hierarchical methods developed for single agent systems be extended to multi-agent systems? -There are some results on the complexity of hierarchical problem solving in evolutionary algorithms. Can we generalize those results to other fields in which hierarchy is important? -What is the relationship between hierarchical methods and "flat", "monolithic" methods which do not exploit hierarchical structure, both in terms of the type of solutions and in terms of the savings that can be obtained with hierarchical methods? -There exist mathematically sound methods for learning policies given a hierarchical structure, for example in reinforcement learning. Can we provide similarly sound methods for learning the hierarchical structure itself? -Hierarchical solutions sometimes perform suboptimally. Can these losses as a result of hierarchy be formalized, and can solutions be guaranteed that are optimal given the hierarchical structure? -What are the most important questions future research on hierarchical methods should address? -Applications of hierarchical methods on complex/real-world problems. ------------------------------------------------------------------------ Date: Tue, 03 Jan 2006 09:19:28 +0100 From: Peter A.N. Bosman <Peter.Bosman@...> To: ml@... Subject: OBUPM-2006 Workshop at GECCO 2006 Workshop on Optimization by Building and Using Probabilistic Models http://minner.bwl.uni-mannheim.de/obupm06/ to be held as part of the 2006 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE (GECCO-2006) July 8-12, 2006 (Saturday-Wednesday) Renaissance Seattle Hotel, Seattle, Washington, USA Organized by ACM SIG-EVO: www.sigevo.org/GECCO-2006 Genetic- and evolutionary algorithms (GEAs) evolve a population of candidate solutions to a given optimization problem using selection and variation. Two variation operators are common in current genetic- and evolutionary computation crossover and mutation. One way to make variation operators more powerful and flexible is to build a probabilistic model of the selected promising solutions and sample the model to generate a new population of candidate solutions. The purpose of this workshop is to present and discuss recent advances in such methods, new theoretical and empirical results, applications, and promising directions for future research. The OBUPM-2006 workshop has a specific focus on continuous optimization. Most work in the OBUPM area, and the most promising results, has been on discrete optimization using discrete representations. An interesting topic is how these successes can be carried over to continuous optimization. The workshop welcomes papers on any aspect of this topic, including single-objective and multi-objective optimization. To submit your contribution, send your paper in Postscript or PDF by e-mail to Peter.Bosman@.... Failure to comply with the ACM formatting rules will result in exclusion from the proceedings. Please see: http://www.sigevo.org/gecco-2006/submitting.html March 12, 2006: Paper submission deadline April 1, 2006: Notification of acceptance April 19, 2006: Camera-ready copy deadline Please check http://minner.bwl.uni-mannheim.de/obupm06/ for updates. Contact a workshop organizer with questions. ------------------------------------------------------------------------ Date: Wed, 4 Jan 2006 20:11:32 +0900 From: Ajith Abraham <abraham.ajith@...> To: Computational Intelligence <computational.intelligence@...> Subject: Book Chapters on Hybrid Evolutionary Systems Hybrid Evolutionary Systems -- Springer SCI Series http://www.softcomputing.net/cec06/ Evolutionary Computation has become an important problem solving methodology among many researchers working in the area of computational intelligence. The population based collective learning process, self adaptation and robustness are some of the key features of evolutionary algorithms when compared to other global optimization techniques. Evolutionary computation has been widely accepted for solving several important practical applications in engineering, business, commerce, etc. As we all know, the problems of the future will be more complicated in terms of complexity and data volume. Hybridization of evolutionary algorithms is getting popular due to its capabilities in handling several real world problems involving: complexity, noisy environment, imprecision, uncertainty and vagueness. A fundamental stimulus to the investigations of hybrid approach is the awareness that combined approaches will be necessary to solve some of the real world problems. This edited volume is targeted to present the latest state-of-the-art methodologies in 'Hybrid Evolutionary Systems'. Editors invite authors to submit their original and unpublished work that communicates current research on 'Hybrid Evolutionary Systems', regarding both the theoretical and methodological aspects, as well as various applications to many real world problems from science, technology, business or commerce. The book is intended to be published in the Springer Verlag Series 'Studies in Computational Intelligence'. Authors should submit original and unpublished work by email to computational.intelligence@.... Papers must be no more than 40 pages in length. Abstract: January 15, 2006 Chapter Submission: February 28, 2006 Notification of Acceptance: April 30, 2006 Camera-ready Submission: June 15, 2006 Publication: September 2006 Please direct all queries to <computational.intelligence@...> ------------------------------------------------------------------------ Date: Wed, 4 Jan 2006 19:40:44 -0800 From: Moises Goldszmidt <moises.goldszmidt@...> To: ml@... Subject: Tackling Computer Systems Problems with Machine Learning First Workshop on Tackling Computer Systems Problems with Machine Learning Techniques (SysML) (Co-located with SIGMETRICS 2006) June 27, 2006 Saint-Malo, France http://research.microsoft.om/workshops/sysml/ Recently, more and more computer systems researchers are borrowing machine learning techniques to attack problems in real-world computer systems, from reliability and performance issues in large-scale systems and networks to power efficiency in sensor networks and self-configuration in complicated systems. The motivation is simple: building empirical models based on statistical pattern recognition, data mining, probabilistic reasoning and other machine learning methods promises to help us cope with the challenges of scale and complexity of current and future systems. The goal of this workshop is to bring together researchers applying machine learning techniques to a wide-range of real-world computer systems and researchers making sure that measurements are robust and error free and that system performance models are sound. The objectives are cross-pollination, perspective on the hard problems and opportunities, as well as discussion of evaluation and validation methodologies. To this end, we would like to include the diverse spectrum of systems-related fields, including communication networks, computer architecture, databases, distributed systems, and operating systems. Regardless of the specific domain, applying machine learning techniques requires us to deal with many similar issues, for collecting training data and interpreting algorithm results to managing false positives and determining our confidence in inferences drawn from empirical models. We believe the lessons learned in the context of one system can give insights to applying machine learning to another. We invite authors to submit short position papers or reports of early work related to current and future applications of machine learning techniques to solving computer systems problems. Topics of interest include, but are not limited to: -Use of machine learning techniques to address reliability, performance, security, or manageability issues in computer systems -New applications of machine learning to computer systems problems -Challenges of scale in applying machine learning to large systems -Experience with on-line data collection and machine learning analysis -Integration of machine learning into real-world systems and processes We particularly encourage papers describing experience with real-world systems and lessons applicable across a variety of computer systems. Submitted papers must be no longer than 5 two-column pages (10pt font, 1 inch margins), including all figures and references. The review process is not blind. Author names and affiliations should be included on the first page. Details on the submission process will be made available in January. Submissions due: March 3, 2006 Notification of acceptance: April 14, 2006 Camera-ready copy due: May 1, 2006 Workshop: June 27, 2006 ------------------------------------------------------------------------ Date: Wed, 4 Jan 2006 11:17:28 +1100 From: Menno van Zaanen <menno@...> To: ml@... Subject: ICGI 2006 ICGI 2006: 8th International Colloquium on Grammatical Inference http://www.tnlab.ice.uec.ac.jp/icgi06/ icgi06@... The University of Electro-Communications, Chofu, Tokyo 182-8585, JAPAN September 20 (Wednesday) - 22 (Friday), 2006 ICGI-2006 is the eighth in a series of successful biennial international conferences in the area of grammatical inference. Grammatical inference has been extensively addressed by researchers in information theory, automata theory, language acquisition, computational linguistics, machine learning, pattern recognition, computational learning theory, and neural networks. ICGI-2006 will be the first conference in this series to be held in Asia. Further, as in the previous ICGI conference, we are planning to hold a grammatical inference competition that will be known as the Tenjinno competition as part of ICGI-2006. The conference seeks to provide a forum for presentation and discussion of original research papers on all aspects of grammatical inference including, but not limited to: * Different models of grammar induction * Algorithms for induction of different classes of languages/automata * Theoretical and experimental analysis of different approaches * Broader perspectives on grammar induction Particular emphasis will be given to papers presenting work on innovative applications of grammar induction in natural language acquisition, computational biology, Web mining, structural pattern recognition, information retrieval, text processing, adaptive intelligent agents, systems modelling and control, and other domains. ICGI-2006 will be held in Chofu, Tokyo. The conference will be located in The University of Electro-Communications (UEC) (http://www.uec.ac.jp/eng/). All paper submissions, review and notification of acceptance will be done electronically through the conference's WWW pages (http://www.tnlab.ice.uec.ac.jp/icgi06/). Submission of manuscripts: May 20, 2006 Notification of acceptance: June 19, 2006 Final version of manuscript: July 16, 2006 ------------------------------------------------------------------------ Date: Wed, 4 Jan 2006 11:12:19 +1100 From: Menno van Zaanen <menno@...> To: ml@... Subject: Tenjinno Machine Translation Competition Tenjinno Machine Translation Competition http://www.ics.mq.edu.au/~tenjinno/ Tenjinno is a competition held in conjunction with the 8th International Colloquium on Grammatical Inference (ICGI 2006) that combines grammatical inference with machine translation. The task is to create a machine translation system using a set of training sentences and to use the model to translate a set of test sentences. The Tenjinno competition differs from other machine translation competitions in that the data is artificial and generated from an underlying formal model. The Tenjinno machine translation competition aims to measure and improve upon the current state-of-the-art in grammatical inference. Tenjinno is the successor to the earlier Abbadingo, Gowachin, and Omphalos competitions. Information on how the data is generated and ideas on how to tackle these problems can be found on the Tenjinno website together with other information: http://www.ics.mq.edu.au/~tenjinno/ Tenjinno defines a problem that ranges over several fields. As such, we encourage submission from practitioners from all areas of computer science including (but not limited to): - machine learning, - natural language processing, - formal languages, - machine translation, and - bioinformatics. 31 December 2005 Competition details available 1 January 2006 Competition begins 1 July 2006 Competition closes 2 July 2006 Competition winner announced September 2006 Tenjinno session at ICGI-2006 For any comments or questions please contact the Tenjinno organisers at tenjinno@.... ------------------------------------------------------------------------ Date: Tue, 10 Jan 2006 16:54:49 -0500 (EST) From: mlittman@... (Michael L. Littman) To: ml@... Subject: ICML 2006 Call for Workshops/Tutorials and Papers ICML 2006 23rd International Conference on Machine Learning www.icml2006.org ICML 2006 invites submission of papers in all aspects of machine learning. We welcome submissions of creative, innovative work on systems that are self adaptive; systems that improve their own performance; or systems that apply logical, statistical, probabilistic or other formalisms to analysis of data, learning predictive models, or interaction with the environment. We welcome submissions that are primarily theoretical contributions; we welcome carefully evaluated empirical studies; and we particularly welcome work that combines both features. We also encourage submissions that bridge the gap between the central disciplines of machine learning and other fields of research. The 23rd International Conference on Machine Learning (ICML'06) is also soliciting proposals for high-quality workshops and tutorials to be hosted at the conference. For administrative details, please visit the URLs: http://www.icml2006.org/icml2006/workshops.html (workshops) and http://www.icml2006.org/icml2006/tutorials.html (tutorials). Tutorial proposals due: NOW Jan 20, 2006 Workshop proposals due: NOW Jan 20, 2006 PLEASE SUBMIT! Abstracts due: Jan 30, 2006 Full submissions due: Feb 6, 2006 ICML Conference: Jun 26-28, 2006 For more information, please visit http://www.icml2006.org/icml2006/ ------------------------------------------------------------------------ Date: Mon, 9 Jan 2006 17:56:54 -0500 From: Ron Sun <rsun@...> To: ml@... Subject: CogSci 2006 CogSci 2006 The Twenty-Eighth Annual Conference of the Cognitive Science Society July 27-30, 2006 Tutorials/workshops day: July 26 in cooperation with the 5th International Conference on Cognitive Science (Asia-Pacific) Sheraton Vancouver Wall Centre, Vancouver, Canada http://www.cogsci.rpi.edu/~rsun/cogsci2006/ We invite submissions to the Twenty-Eighth Annual Conference of the Cognitive Science Society, the premier series of conferences in cognitive science. Each year, in addition to submitted papers, we invite speakers who help to highlight some aspects of cognitive science. This year, we highlight Learning: Tackling Both Implicit and Explicit Processes. Invited symposia will provide more explorations of the topics: 1. The Synergy between Implicit and Explicit Learning Processes 2. The Emerging Learning Sciences Paper Submissions due: February 1, 2006 Acceptance notifications: April 15, 2006 Camera-ready copies due: May 15, 2006 ------------------------------------------------------------------------ Date: Wed, 11 Jan 2006 18:07:29 +0100 From: Bertram Fronhoefer <Bertram.Fronhoefer@...> To: ml@... Subject: ICCL Summer School on Knowledge Structures ICCL Summer School 2006: Knowledge Structures Technische Universitt Dresden June 24 - July 8, 2006 http://www.computational-logic.org/iccl-ss-2006 The topic of this year's summer school is Knowledge Structures. It is common wisdom that the still growing power of digital data processing greatly enhances the wealth of human knowledge and will continue to do so. A precondition for this is, however, that knowledge is encoded and represented in a computer-accessible manner, such that it can be algorithmically processed. This requires, in turn, the use of appropriate formal structures for knowledge representation and knowledge processing. Such structures, called `Knowledge Structures', will be the topic of this year's ICCL summer school. There are many approaches to this topic ranging from formal logics, to mathematical and data mining methods. The summer school's focus is on the following three areas: 1. Logic, with Description Logic and Inductive Logic Programming, 2. Cluster Methodology, with applications to text clustering and Semantic Web mining, and 3. Formal Concept Analysis, with applications to Ontologies and Machine Learning. The basic ideas of these areas will be introduced and discussed, with the aim of providing a broad methodological repertoire for future research and applications. If you want to attend the summer school, we prefer that you register by March 18, 2006, at the web page mentioned above. For all who want to apply for a grant, this deadline is obligatory. After March 18, 2006, registration will be possible as long as there are vacant places, but attendance will be limited to about 60 people. We ask for a participation fee of 150 EUR. A limited number of grants may be available, please indicate in your application if the only possibility for you to participate is via a grant. Applications for grants must include an estimate of travel costs and they should be sent together with the registration. People applying until March 18, 2006, and applying for a grant will be informed about respective decisions on grants by end of March 2006. It will be possible for some participants to present their research work during a small workshop integrated in the summer school. If you would like to do so, please register by means of the online workshop registration form on the web page mentioned above: (The title of your proposed talk, and, in addition, an extended abstract or a full paper of at most 10 pages in postscript or pdf format must be submitted by March 18, 2006.) Notification of acceptance of a talk at the integrated workshop will be by April 24, 2006. Please note that participation at the summer school is a prerequisite for participation at the workshop. ------------------------------------------------------------------------ Date: Tue, 17 Jan 2006 17:11:21 +0100 From: Computational Philosophy Laboratory <cp-lab@...> To: undisclosed-recipients: ; Subject: ECAI2006 Workshop Abduction and Induction CALL FOR PAPERS: ECAI 2006 Workshop on Abduction and Induction in AI and Scientific Modelling Riva Del Garda, Trentino, Italy August 29, 2006 http://www.doc.ic.ac.uk/~or/AIAI06/ Abduction and induction are forms of logical reasoning with incomplete information that have many applications in AI. Abduction reasons from effects to possible causes and has been used in tasks such as planning and diagnosis. Induction learns general rules for observed data and is typically used for classification and knowledge acquisition. As our understanding of abduction and induction continues to grow and our computational methods improve, it is becoming apparent that there are potentially significant benefits to be gained by integrating them both in an incremental cycle of knowledge development. By providing a means of extending prior knowledge in the light of new experience, such techniques could be useful in scientific and other AI modelling applications. Indeed, some promising results are beginning to emerge from the very first tentative applications of such hybrid systems. The purpose of this workshop is to identify novel techniques for the integration of abduction and induction, and to explore the practical utility of such methods in scientific and other modelling domains. The primary aims are: 1) To better understand the role of abduction and induction in theory formation and revision; and to explore methods for combining them both within an incremental cycle of knowledge development; 2) To identify different conceptual models for integrating abduction and induction and to investigate how this integration can be done in a computationally viable way; 3) To determine the benefits that could result from the combination of abduction and induction and to characterise the classes of problems that can be usefully solved with such techniques; 4) To examine possible application areas (such as systems biology) and to assess in more detail the utility of such integrated frameworks. The workshop will also aim to examine the relations to other approaches (philosophical or cognitive) for modelling scientific and other domains. Please send pdf papers via email to "or@..." with the subject "aiai06submission". Submissions should be sent by the 5th of April. Authors will be notified of acceptance/rejection by the 5th of May. Jan 10th, 2006 Call for papers Apr 5th, 2006 Paper submission deadline May 5th, 2006 Notification of acceptance May 18th, 2006 Early registration deadline May 20th, 2006 Camera ready copy deadline Aug 29th, 2006 Date of the Workshop For more information, please see http://www.doc.ic.ac.uk/~or/AIAI06/ ------------------------------------------------------------------------ Date: Sat, 14 Jan 2006 16:31:24 -0600 (CST) From: Jiawei Han <hanj@...> To: ml@... Subject: New Journal---ACM Transactions on Knowledge Discovery from Data Call for papers: ACM Transactions on Knowledge Discovery from Data Journal Web site: http://www.acm.org/tkdd (available very soon) Journal Alternative Web site: http://tkdd.cs.uiuc.edu/ Author information: http://tkdd.cs.uiuc.edu/authors.html Research paper submission Web site: http://mc.manuscriptcentral.com/tkdd Knowledge discovery and data mining has become a dynamic, strong, and interdisciplinary research field, representing the confluence of statistical data analysis, machine learning, database systems, data warehousing, scalable algorithms, high-performance computing, and various data-intensive applications. The field promotes the research and development of effective and scalable methods for discovery of interesting patterns and knowledge from data, and has attracted great attention in research communities, high-tech industry, application users, and the general public. The rapid development of the field has been due to the tremendous increase in the amount of data collected with the advent of World-Wide Web and the concomitant developments in computer, data collection, and information management technologies, and the imminent need to analyze such data and turn it into knowledge. To promote research in this field, the ACM Publication Board has decided to launch a new journal, ACM Transactions on Knowledge Discovery from Data (TKDD). The journal will publish high quality research papers in the area of data mining and knowledge discovery, on the principles, algorithms, methods, systems, and applications of knowledge discovery and data mining. It will concentrate on papers that have practical relevance to the construction, evaluation, application and use of knowledge discovery and data mining systems and the infrastructure to support these. The style of this ACM journal is similar to many other ACM Transactions, such as TODS (Transactions on Database Systems), TOIS (Transactions on Information Systems), and TOIT (Transactions on Internet Technology). The transactions will consist primarily of high-quality regular research contributions. This is an archival journal and it is intended that the papers will have lasting importance and value over time. The journal expects to publish, at steady state, 4-5 papers per issue and 4 issues per year. The first issue of the journal is expected to appear in the first quarter of 2007. The Web site of the TKDD submssion is: http://mc.manuscriptcentral.com/tkdd Please consult the Web site for detailed information for authors and the submission procedures. ------------------------------------------------------------------------ Date: Mon, 16 Jan 2006 11:31:47 +0000 From: Stephen Smith <sls5@...> To: ml@... Subject: MedGEC - GECCO Workshop on Medical Applications of Genetic and Evolutionary Computation We encourages researchers to submit papers to MedGEC 2006, the GECCO Workshop on Medical Applications of Genetic and Evolutionary Computation to be held as part of the 2006 Genetic and Evolutionary Computation Conference (GECCO-2006) July 8-12, 2006 (Saturday-Wednesday) Renaissance Seattle Hotel, Seattle, Washington, USA Organized by ACM SIG-EVO. Full details can be found at the MedGEC Web site: http://www.elec.york.ac.uk/intsys/events/MedGEC2006/home.htm Accepted papers will be considered for inclusion in a special issue of the journal "Genetic Programming and Evolvable Machines". Subjects will include (but are not limited to) applications of GEC to: Medical imaging, Medical signal processing, Clinical diagnosis and therapy, Data mining medical data and records, Clinical expert systems, Modeling and simulation of medical processes. A dedicated workshop at GECCO provides a much needed focus for medical related Applications of EC, not only providing a clear definition of the state of the art, but also support to practitioners for whom GEC might not be their main area of expertise or experience. The Workshop has two main aims: (i) to provide delegates with examples of the current state of the art of applications of GEC to medicine. (ii) to provide a forum in which researchers can discuss and exchange ideas, support and advise each other in theory and practice. Paper submission deadline: 1 March, 2006 Notification of acceptance: 29 March, 2006 Camera-ready copy deadline: 12 April, 2006 Workshop: 8 July, 2006 (provisional date) For full details, please see the Workshop home page at: http://www.elec.york.ac.uk/intsys/events/MedGEC2006/ ------------------------------------------------------------------------ Date: Tue, 17 Jan 2006 14:54:32 +0100 From: ISMIS 2006 <ismis2006@...> To: undisclosed-recipients Subject: ISMIS 2006 ISMIS 2006: Call for Paper 16th International Symposium on Methodologies for Intelligent Systems Bari, Italy, September 27-29, 2006 http://www.di.uniba.it/ismis2006/ imsis2006@... Paper submission:.................. March 18 Notification of acceptance:........ May 15 Camera-ready copy due:............. June 30 ISMIS 2006 invites submissions of original research contributions, as well as proposals for panels and workshops. Contributions for industry and applications sessions and software demonstrations also are solicited. The conference covers a broad range of topics, including the use of conventional approaches, as well as new challenges for advanced techniques for intelligent systems in any possible domain. This Symposium is intended to attract individuals who are actively engaged both in theoretical and practical aspects of intelligent systems. The goal is to provide a platform for a useful exchange between theoreticians and practitioners, and to foster the cross-fertilization of ideas in the following areas: Active Media Human-Computer Interaction Autonomic and Evolutionary Computation Intelligent Agent Technology Intelligent Information Retrieval Intelligent Information Systems Intelligent Interfaces Knowledge Representation and Integration Knowledge Discovery and Data Mining Logic for AI and Logic Programming Machine Learning Soft Computing Text Mining Web Intelligence In addition, we solicit papers dealing with Applications of Intelligent Systems in complex/novel domains, e.g., bioinformatics, global change, manufacturing, health care, etc. Any necessary information concerning typesetting can be obtained from Springer-Verlag page at http://www.springer.de/comp/lncs/authors.html. Detailed paper instructions are provided on the conference homepage at http://www.di.uniba.it/ismis2006/ The ISMIS 2006 Staff ------------------------------------------------------------------------ Date: Wed, 18 Jan 2006 16:29:30 +0100 (MET) From: juffi@... To: ml@... Subject: ECML-2006/PKDD-2006 Call for Papers ECML-2006/PKDD-2006 http://www.ecmlpkdd2006.org/ Berlin, Germany, September 18-22, 2006 The 17th European Conference on Machine Learning (ECML) and the 10th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD) will be co-located in Berlin, Germany, September 18-22, 2006. The combined event will comprise presentations of contributed papers and invited speakers, a wide program of workshops and tutorials, and a discovery challenge. Abstract submission deadline: April 2006 Paper submission deadline: May 2006 Acceptance notification: June 2006 Camera-ready copies due: June 2006 A separate call for proposals will follow for workshops and tutorials, which will be held on September 18 and 22. The main conference will probably start in the afternoon of September 18 and end at noon on September 22. The conferences welcome high-quality research contributions pertinent to any aspects of machine learning and knowledge discovery, ranging from principles to practice; particular attention will be paid to papers describing innovative, challenging applications. There will be a single electronic submission procedure, where authors must indicate whether they are submitting their paper to ECML or PKDD. There will be a joint programme committee consisting of area chairs and reviewers for both conferences. In order to allow a meaningful assignment of papers to the most suitable area chair and reviewers, you should indicate content with a suitable set of keywords. Student submissions should be clearly indicated on the submission form. The papers must be in English and must be formatted according to the Springer-Verlag Lecture Notes in Artificial Intelligence guidelines. Authors instructions and style files can be downloaded at http://www.springer.de/comp/lncs/authors.html. In this format the maximum length of papers is 12 pages. Double submissions to the KDD conference are allowed. ------------------------------------------------------------------------ Date: Wed, 12 Oct 2005 00:02:51 +0100 From: Jorge Tavares <jast@...> To: ml@... Subject: EvoOpt 2006 2nd CALL FOR PAPERS EvoOpt 2006 Special Track on Evolutionary Optimization at the 19th International FLAIRS Conference (in cooperation with the American Association for Artificial Intelligence) 11th-13th May, 2006, Melbourne, Florida, USA EvoOpt 2006 website: http://evoopt2006.dei.uc.pt FLAIRS 2006 website: http://www.indiana.edu/~flairs06/ Submission deadline: November 21, 2005 Notification of acceptance: January 20, 2006 Camera ready papers: February 13, 2006 EvoOpt 2006: May 11-13, 2006 ------------------------------------------------------------------------ Date: Tue, 18 Oct 2005 18:38:35 +0800 (HKT) From: ssspr06@... To: ml@... Cc: ssspr06@... Subject: S+SSPR 2006 JOINT IAPR INTERNATIONAL WORKSHOPS ON Structural and Syntactic Pattern Recognition (SSPR 2006) and Statistical Techniques in Pattern Recognition (SPR 2006) August 17-19, 2006 Hong Kong University of Science and Technology, China Web site: http://www.ssspr.org/2006/ Paper submission deadline: January 31, 2006 ------------------------------------------------------------------------ Date: Sat, 22 Oct 2005 10:51:06 +0200 From: Lorenzo Magnani <lmagnani@...> To: undisclosed-recipients:; Subject: MBR06_CHINA MODEL-BASED REASONING IN SCIENCE AND MEDICINE The Second International Conference of Philosophy and Cognitive Science MBR'06_CHINA Guangzhou (Canton), China, July 3-5, 2006 Submission deadline............................12 February 2006 Notification of acceptance.................... 19 April 2006 Conference.....................................3-5 July 2006 Final papers due................................31 August 2006 CONFERENCE SITE: http://www.unipv.it/webphilos_lab/mbr06.php ------------------------------------------------------------------------ Date: Thu, 3 Nov 2005 12:11:27 -0000 From: Alex Freitas <A.A.Freitas@...> To: ml@... Subject: UK KDD Symposium (UKKDD'06) UK KDD SYMPOSIUM (UKKDD'06) http://www2.cmp.uea.ac.uk/Research/kdd/ukkdd06/ukkdd06.html Wednesday 26 April 2006 John Innes Conference Centre, Norwich ------------------------------------------------------------------------ Date: Mon, 19 Dec 2005 17:40:43 -0800 From: Pedro Domingos <pedrod@...> To: ml@... Subject: The Alchemy system for statistical relational AI The Alchemy system for statistical relational AI is now available in beta at: http://www.cs.washington.edu/ai/alchemy Alchemy provides a series of algorithms for statistical relational learning and probabilistic logic inference, based on Markov logic. It allows you to easily develop applications like: - collective classification - link prediction - entity resolution - social network modeling and many others. The current version includes: - discriminative weight learning - generative weight learning - structure learning - MAP/MPE inference - MCMC (Gibbs sampling) inference ------------------------------------------------------------------------ Date: Thu, 13 Oct 2005 08:29:28 +0200 (CEST) From: Samy Bengio <bengio@...> To: ml@... Subject: Two open PhD positions in machine learning at IDIAP The IDIAP Research Institute seeks two qualified candidates for PhD positions in machine learning. The objective of the first project is to develop novel kernel based algorithms for the analysis of sequences of high level events, such as automatic speech recognition (ASR). State-of-the-art ASR systems are based on generative Hidden Markov Models (HMMs). On the other hand, recent machine learning research have shown promising results in kernel based large margin discriminant models such as Support Vector Machines (SVMs) which maximize the margin between positive and negative examples. More recently, new kernels were proposed for various time-series tasks. The objective of this project is to study how these kernels could be modified in the context of more complex temporal tasks such as speech and video understanding. The objective of the second project is to develop novel machine learning algorithms for multi-channel sequence processing. Modeling jointly several sources of information (recorded from several cameras, microphones, etc.) has several practical applications, including audio-visual speech recognition, multimodal person tracking, or complex scene analysis. Several machine learning models have already been proposed for such task, mainly for the case of two channels. The goal of this project is to propose theoretical and applied solutions for the case of more than two (potentially asynchronous) channels. Generative (Markovian based) models as well as margin-based models will be considered for the task. Ideal candidates will hold a degree in computer science, statistics, or related fields. She or he should have strong background in statistics, linear algebra, signal processing, C++, Perl and/or Python scripting languages, and the Linux environment. Knowledge in statistical machine learning and speech processing is an asset. Appointment for a PhD position is for a maximum of 4 years, provided successful progress, and should lead to a dissertation. Annual gross salary ranges from 36,000 Swiss Francs (first year) to 40,000 Swiss Francs (last year). Starting date is immediate. IDIAP is an equal opportunity employer and is actively involved in the European initiative involving the Advancement of Women in Science. IDIAP seeks to maintain a principle of open competition (on the basis of merit) to appoint the best candidate, provides equal opportunity for all candidates, and equally encourages both females and males to consider employment with IDIAP. Although IDIAP is located in the French part of Switzerland, English is the main working language. Free English and French lessons are provided. Interested candidates should send a letter of motivation, along with their detailed CV and names of 3 references to jobs@.... More information can also be obtained by contacting Samy Bengio, Senior Researcher in Machine Learning at: IDIAP, CP 592, rue du Simplon 4, 1920 Martigny, Switzerland.tel: +41 27 721 77 39, fax: +41 27 721 77 12. mailto:bengio@..., http://www.idiap.ch/~bengio ------------------------------------------------------------------------ Date: Mon, 24 Oct 2005 08:05:27 -0700 From: Thomas Dietterich <tgd@...> To: ml@... Subject: Postdoc positions at Oregon State University Oregon State University School of Electrical Engineering and Computer Science One or more Research Associate positions in the Machine Learning, Computer Graphics, and Computer Vision groups starting January 2006. Required qualifications include a Ph.D. in computer science or related field; strong mathematical background; experience with at least 3 of the following: (a) knowledge representation frameworks (logical and probabilistic), (b) reasoning methods (logical and probabilistic), (c) experimental machine learning research, (d) planning and reasoning algorithms, (e) virtual environments for training, (f) computer vision for object recognition and tracking, (g) augmented reality; excellent written and spoken communication skills; excellent programming and software engineering skills; excitement about computer science research; and the ability to manage graduate and undergraduate students working on research projects. Position is full-time, 12 month, f |
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