Machine Learning List: Volume 18, Number 2, Monday, February 13, 2006 ************************************************************************ Contents Calls for Papers & Participation ECML/PKDD-06 Berlin ECML/PKDD-2006 Call for Tutorials and Workshops Workshop on Machine Learning in Structural and Systems Biology SIGKDD Explorations: Successful Real-World Data Mining Applications SEAL06 Analysis of Environmental Data ACM SIGKDD 2006 June 26-29, WORLDCOMP'06 An International Symposium ECAI06 Workshop on Neural-Symbolic Learning and Reasoning FOCA@ESSLLI 2006 "Multi-objective Machine Learning" deadline extension KES2006 deadline extension Special issue of Data Mining and Knowledge Discovery IDAMAP 2006 Career Opportunities PhD research assistantships in machine learning at OGI Open position at ISLE ************************************************************************ The Machine Learning List is moderated. Contributions should be relevant to the scientific study of machine learning. Please send submissions for distribution to: ml@isle.org. For requests to be added, removed, or to change your email address, send email to: ml-request@isle.org. 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: Wed, 18 Jan 2006 16:29:30 +0100 (MET) From: juffi@ke.informatik.tu-darmstadt.de To: ml@isle.org Subject: ECML/PKDD-06 Berlin Call for Papers ECML/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: 26 April 2006 Paper Submission deadline: 03 May 2006 Acceptance Notification: 14 June 2006 Camera-ready copies due: 30 June 2006 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. The maximum length of papers is at most 12 pages in this format. Double submissions to the KDD conference are allowed. ------------------------------------------------------------------------ Date: Mon, 30 Jan 2006 15:14:04 +0200 (EET) From: Tapio Elomaa To: ml@isle.org Subject: ECML/PKDD-2006 Call for Tutorials and Workshops The 17th European Conference on Machine Learning (ECML) and The 10th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD) Berlin, Germany, Sept. 18-22, 2006 http://www.ecmlpkdd2006.org/. The ECML/PKDD-2006 Organizing Committee invites proposals for tutorials and workshops that will be co-located with the main ECML/PKDD-2006 conference. We invite proposals for half-day tutorials and full day workshops. Workshop Dates Proposal deadline March 31, 2006 Acceptance notification April 21, 2006 Call for Papers on the web May 5, 2006 Paper submission deadline June 28, 2006 Proceedings (camera-ready) August 16, 2006 Tutorial Dates Proposal deadline March 31, 2006 Acceptance notification April 21, 2006 Tutorial summary on the web May 15, 2006 Tutorial notes (camera-ready) August 16, 2006 For more information and detailed instructions on proposing a tutorial or a workshop see http://www.ecmlpkdd2006.org/workshops.htm or contact the tutorial and workshop chairs. ------------------------------------------------------------------------ Date: Sat, 21 Jan 2006 19:46:59 +0200 From: Esa Pitknen To: ml@isle.org Subject: Workshop on Machine Learning in Structural and Systems Biology CALL FOR PAPERS Workshop on Probabilistic Modeling and Machine Learning in Structural and Systems Biology http://www.cs.helsinki.fi/group/bioinfo/events/pmsb06/ Tuusula, Finland, 17-18 June 2006 The increasing amount of biological data, the development of genome-wide measurement technologies, and the shift from the study of individual genes to systems view all contribute to the need to develop computational techniques for learning models from data. At the same time, the increase in computational resources has enabled the adoption of more realistic modeling methods. The aim of this workshop is to provide a broad look at the state of the art in the probabilistic modeling and machine learning methods that involve biological structures and systems, and to bring together method developers and experimentalists working on the problems. We encourage submissions that bring forward methods for discovering complex structures (e.g. interaction networks, molecule/cellular structures) and methods supporting genome-wide data analysis. A non-exhaustive list of topics suitable of this workshop include: Methods: Algorithms, Bayesian methods, Data integration/fusion, Feature/subspace selection, High-throughput methods, Kernel methods, Machine learning, Probabilistic inference, and Structured output prediction. Applications: Sequence annotation, Gene expression, Gene networks, Gene prediction, Metabolic profiling, Metabolic reconstruction, Protein structure prediction, Protein function prediction, and Protein-protein interaction networks. We invite submissions of extended abstracts, no more than four pages, formatted according to the Springer Lecture Notes in Computer Science style, to the email address juho.rousu at cs.helsinki.fi Abstract submission deadline April 23, 2006 Notification of acceptance May 7, 2006 Final version due May 31, 2006 ------------------------------------------------------------------------ Date: Sun, 22 Jan 2006 12:51:10 -0700 From: Osmar Zaiane To: zaiane@cs.ualberta.ca Subject: SIGKDD Explorations: Successful Real-World Data Mining Applications SIGKDD Explorations 2006 June Issue Call for Papers Special Issue on Successful Real-World Data-Mining Applications Submissions April 3, 2006 Notification and Reviews May 1, 2006 Camera-ready due May 15, 2006 Issue Publication June 2006 This special issue invites submissions concerning successful application of data-mining techniques in industry, from marketing to drug research. Papers should report on real-world data-mining projects that showcase choices, strategies, success, and failure. >From its inception, the field of data mining has been guided by the need to solve practical problems. Successful cases of data-mining application in the industry are motivation and inspiration not only to industry but also to research. This special issue will highlight some of the best deployed data-mining systems. Most operational industrial and scientific systems that involve data mining to some extent are likely to be acceptable. Systems that are responsible for mission critical systems, medical applications, cash flow, or applications that significantly benefit humanity will be particularly good candidates. If you are unsure about the suitability of your paper, please contact the editors with at the email address indicated below. Topics include but are not limited to: Genomics; Inventory control; Customer relationship management; ShopBots; Recommendation systems; Auction trading systems; Clinical patient monitoring; Seismic data interpretation; Survival analysis for medical procedures; Climate analysis; Correlating genes with disease; Dangerous drug interactions; Law enforcement applications; Search engine marketing; Food spoilage elimination; Price optimization; Data visualization in mission-critical user interfaces; Text processing. Submissions should be made to zaiane[_at_]cs.ualberta.ca, preferably in a PDF format and should not exceed 8 pages. In addition, please email the abstract in text format. Detailed formatting instructions are available from http://www.acm.org/sigs/sigkdd/explorations/submissions.php ------------------------------------------------------------------------ Date: Tue, 24 Jan 2006 22:33:03 +0800 From: Wenjian Luo To: ml@isle.org Subject: SEAL06 The Sixth International Conference on Simulated Evolution And Learning 15-18 October 2006, Hefei, Anhui, China http://nical.ustc.edu.cn/seal06/ Evolution and learning are two fundamental forms of adaptation. SEAL'06 is the sixth biennial conference in the successful series that aims at exploring these two forms of adaptation and their roles and interactions in adaptive systems. Cross-fertilization between evolutionary learning and other machine learning approaches, such as neural network learning, reinforcement learning, decision tree learning, and fuzzy system learning, will be strongly encouraged by the conference. The other major theme of the conference is optimization by evolutionary and other nature inspired approaches. All accepted papers that are presented at the conference will be included in the conference proceedings, published by Springer in their Lecture Notes in Computer Science series. The best papers will be invited to submit extended results to special issues of Genetic Programming and Evolvable Machines, Connection Science, International Journal of Computational Intelligence and Applications, and Journal of Computer Science and Technology. Special sessions and tutorials will be organized at the conference. The conference is calling for special session and tutorial proposals. The tutorials will be offered on 15 Oct 2006. ------------------------------------------------------------------------ Date: Wed, 25 Jan 2006 19:23:52 +0100 (CET) To: undisclosed-recipients@mantra.ijs.si From: aedml@ijs.si (AEDML) Subject: Analysis of Environmental Data You are cordially invited to attend the international seminar on ANALYSIS OF ENVIRONMENTAL DATA WITH MACHINE LEARNING METHODS 27 February - 2 March 2006, Ljubljana, Slovenia http://www-ai.ijs.si/SasoDzeroski/aep/aep.html Organized by Jozef Stefan Institute, Ljubljana, in cooperation with University of Ljubljana and Nova Gorica Polytechnic The seminar will give an introduction to selected machine learning methods as well as illustrative case studies of using these methods to analyze environmental data, such as modeling algal growth in lakes and lagoons, analyzing the influence of physical and chemical parameters on selected bioindicator organisms, and predicting the biodegradability of chemical compounds. The participants will learn to use selected machine learning tools and will have the opportunity for practical work with these tools on real environmental data. The machine learning methods and tools introduced are applicable to data analysis problems from different areas. The seminar is intended for researchers and other professionals in the areas of biology, chemistry, environmental science, and other areas related to ecology and environmental management, whose work requires the analysis of environmental data or modeling ecological processes. For graduate students of the School of Environmental Sciences, Nova Gorica Polytechinc (and cooperating universities) the seminar counts as a specialized elective subject (9 ECTS points). Contents: - Introduction to machine learning: Data mining and knowledge discovery; Evaluating classifiers; Instance-based learning; Introduction to decision trees; Learning classification and regression trees; Learning classification rules; Naive Bayesian classification; Machine discovery of equations; Selecting and combining classifiers - An overview of environmental applications of machine learning: Analysis of the influence of environmental factors on respiratory diseases; Analysis of the influence of soil habitat features on the abundance of Collembola; Modeling phytoplankton growth; Modeling interactions among red deer population, meteorological parameters and new forest growth; - Case studies of using machine learning to analyze ecological data: Analysis of water quality data; Modeling algal growth in the Lagoon of Venice and Lake Bled; Predicting biodegradability of chemical compounds; Runoff prediction from rainfall and past runoff - Demonstrations/hands-on exercises/practical work with machine learning software packages on real ecological data and individual consultations with lecturers - Participant presentations and discussion ------------------------------------------------------------------------ Date: Wed, 25 Jan 2006 14:44:35 -0800 (PST) From: Dimitrios Gunopulos To: ml@isle.org Subject: ACM SIGKDD 2006 KDD-2006 CALL FOR RESEARCH PAPERS THE TWELFTH ACM SIGKDD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING August 20-23, 2006 in Philadelphia, PA http://www.kdd2006.com The ACM SIGKDD conference solicits papers on all aspects of knowledge discovery and data mining. Areas of interest include, but are not limited to: Applications of data mining (biomedicine, business, e-commerce, defense); Data and result visualization; Data warehousing; Data mining for community generation, social network analysis, and graph-structured data; Foundations of data mining; Interactive and online data mining; KDD framework and process; Mining data streams; Mining high-dimensional data; Mining sensor data; Mining text and semi-structured data; Mining multi-media data; Mining uncertain or fuzzy data; Novel data-mining algorithms; Privacy and data mining; Robust and scalable statistical methods; Pre-processing and post-processing for data mining; Security issues; Spatial and temporal data mining Electronic abstract submission: March 3, 2006 Electronic paper submission: March 10, 2006 Author notification: May 23, 2006 Abstracts and full papers must be submitted electronically at the conference Web site (see URL above). Templates are available at http://www.acm.org/sigs/pubs/proceed/template.html. Papers must be submitted in PDF format. Authors are solely responsible for ensuring that their submissions display and print properly. All papers will be judged based on their technical merit, significance, originality, relevance to KDD, and presentation clarity. Papers should describe original work that has not been published before, is not under review elsewhere, and will not be submitted elsewhere during KDD-2006's review period. A separate call is being issued for industrial/government track papers; see the conference URL above. Calls for workshop, tutorial, and panel proposals can also be found at the conference Web site. ------------------------------------------------------------------------ Date: Sun, 29 Jan 2006 09:26:41 +0100 From: Pascal Hitzler To: ml@isle.org Subject: ECAI06 Workshop on Neural-Symbolic Learning and Reasoning Second International Workshop on Neural-Symbolic Learning and Reasoning A Workshop at ECAI2006, Riva del Garda, Italy August 28 or 29, 2006 http://www.neural-symbolic.org/NeSy06/ Artificial Intelligence researchers continue to face huge challenges in their quest to develop truly intelligent systems. The recent developments in the field of neural-symbolic integration bring an opportunity to integrate well-founded symbolic artificial intelligence with robust neural computing machinery to help tackle some of these challenges. The Workshop on Neural-Symbolic Learning and Reasoning is intended to create an atmosphere of exchange of ideas, providing a forum for the presentation and discussion of the key topics related to neural-symbolic integration. Topics of interest include: The representation of symbolic knowledge by connectionist systems; Learning in neural-symbolic systems; Extraction of symbolic knowledge from trained neural networks; Reasoning in neural-symbolic systems; Biological inspiration for neural-symbolic integration; Applications in robotics, semantic web, engineering, bioinformatics, etc. Researchers and practitioners are invited to submit original papers that have not been submitted for review or published elsewhere. Submitted papers must be written in English and should not exceed 6 pages in the case of research and experience papers, and 2 pages in the case of position papers (including figures, bibliography and appendices) in ECAI format. Papers must be submitted directly by email in PDF format to nesy@soi.city.ac.uk Deadline for submission: 15th of April, 2006 Notification of acceptance: 10th of May, 2006 Camera-ready paper due: 17th of May, 2006 ECAI 2006 main conference dates: Aug. 28th to Sept. 1st, 2006. General questions concerning the workshop should be addressed to nesy@soi.city.ac.uk. You are also invited to subscribe to the neural-symbolic integration mailing list at http://www.aifb.uni-karlsruhe.de/mailman/listinfo/nesy ------------------------------------------------------------------------ Date: Tue, 31 Jan 2006 09:26:35 +0100 From: Yaochu.Jin@honda-ri.de To: ml@isle.org Subject: Multi-objective Machine Learning - deadline extension Call for Papers Special Session on "Multi-objective Machine Learning" 2006 International Joint Conference on Neural Networks (part of WCCI'06) July 16-21, Vancouver, Canada http://www.wcci2006.org/ The submission deadline has been extended to February 15, 2006 Machine learning usually has to achieve multiple targets, which are often conflicting with each other. For example in feature selection, minimizing the number of features and the maximizing feature quality are two conflicting objectives. It is also well realized that model selection has to deal with the trade-off between model complexity and approximation or classification accuracy. Traditional learning algorithms attempt to deal with multiple objectives by combining them into a scalar cost function so that multi-objective machine learning problems are reduced to single-objective problems. Recently, there has been increasing interest in applying Pareto-based multi-objective optimization to machine learning, particularly inspired by successful developments in evolutionary multi-objective optimization. The multi-objective approach is particularly successful in: 1) improving the behavior of traditional single-objective machine learning methods; 2) generating diverse multiple Pareto-optimal models for constructing ensembles; and 3) in achieving desirable trade-offs between accuracy and interpretability of neural networks or fuzzy systems. This proposed special session aims to further promote research on multi-objective machine learning by presenting the most recent research results and discussing the challenges in this area. Topics include, but are not limited to: multi-objective clustering, feature extraction and feature selection; multi-objective model selection to improve the performance of learning models, such as neural networks, support vector machines, decision trees, and fuzzy systems; multi-objective model selection to improve the interpretability of learning models, e.g., to extract symbolic rules from neural networks, or to improve the interpretability of fuzzy systems; multi-objective generation of learning ensembles; multi-objective learning to deal with tradeoffs between plasticity and stability, long-term and short-term memories, specialization and generalization; multi-objective machine learning applications All special session papers must be submitted no later than January 31, 2005 through the conference web page at http://139.78.75.247/WCCI-Web_paper_submit.html. Please choose "S.Special Sessions, Sa: Multi-objective machine learning" as your main research topic. ------------------------------------------------------------------------ Date: Fri, 3 Feb 2006 17:05:17 +0100 (CET) From: info@kesinternational.org To: ml@isle.org Subject: KES2006 deadline extension KES2006, the 10th International Conference on Knowledge Based & Intelligent Information & Engineering Systems, Bournemouth, UK October 9-11, 2006 http://kes2006.kesinternational.org GENERAL TRACK SUBMISSION DEADLINE EXTENDED In response to many requests to allow more time for submission at this busy time the deadline has been extended to 15 February 2006. KES2006 will be the latest in the well-established KES International conference series, celebrating a decade of bringing the results of intelligent systems research to the international research community. We are confident that this 10th anniversary will be a very special event. The conference will consist of plenaries, oral presentation sessions, invited sessions and workshops on the applications, tools and theory of intelligent systems. Papers are invited from prospective authors with interests in the indicated conference topics and related areas of application. All contributions should be original and not published elsewhere or submitted for publication during the review period. Please see the Web site for details of the required paper format. To ensure high quality, all papers must be submitted using the PROSE online system, and will be thoroughly reviewed by the KES2006 Program Committee. The conference proceedings will be published by a major publisher. Extended versions of selected papers will be considered for publication in the KES Journal http://www.kesinternational.org/journal/. Authors will be limited to one paper per registration. Scientists, engineers and researchers who would like to organize an invited session of 5/6 papers, or a parallel workshop of a half or full day, on some topic falling within the scope of the conference, are invited to contact the KES Secretariat enclosing the title and content of the proposed session. We also welcome suggestions for other activities that will appeal to our delegates. Submission of papers: 15 February 2006 Notification of acceptance: 1 April 2006 Final papers to be received by: 1 May 2006 Proposals for Invited Sessions / Workshops: 1 February 2006 Session Chair sets Invited Session interim deadlines. Final papers for Invited Sessions musts be received by: 1 May 2006 ------------------------------------------------------------------------ Date: Sun, 5 Feb 2006 12:36:45 -0600 From: Maytal Saar-Tsechansky To: ml@isle.org Subject: Special issue of Data Mining and Knowledge Discovery Call for Papers on Utility-Based Data Mining Special issue of Data Mining and Knowledge Discovery Data mining has made a profound impact on business practices and knowledge management in recent years. Business intelligence has emerged as one of the most popular applications of many data mining techniques. However, as our understanding of data mining improved, it became clear that in order to allow data mining to further its impact on business applications, it would be necessary to align the data mining process and algorithms with the broad economic objectives of the tasks supported by data mining. All the different stages of the data mining process impact the ultimate economic utility derived from the data mining product. The economic utility of acquiring data, extracting a model, and applying the acquired knowledge must be considered. For example, in the data acquisition phase the costs of obtaining informative and accurate data may be considered to help identify the most cost-effective information. Similarly, economic utility also impacts the assessment of the decisions made based on the learned knowledge. Simple assessment measures like predictive accuracy have given way to economic measures, such as profitability and return on investment. Utility-based data mining is a broad topic that covers all aspects of economic utility in data mining. As such, it encompasses the work in cost-sensitive learning and active learning as well as work on the detection of rare events of high value (e.g., anomaly detection). This issue will provide a forum for timely, in-depth presentation of recent advances in utility-based data mining. While economic utility considerations have played a much greater role in predictive data mining tasks, we also encourage papers on the use of economic utility in descriptive tasks. We solicit high-quality, original papers describing work on the following non-exhaustive list of topics: Cost-sensitive learning; Active learning and information acquisition for model induction; Pattern extraction algorithms that incorporate utility considerations; Interaction of economic/utility considerations between various steps in the data mining process (e.g., does misclassification cost affect what type of data should be purchased); Types of economic factors (utility considerations) in data mining and their trade-off; Applications that take into account utility considerations Please follow the submission guidelines: https://www.editorialmanager.com/dami Submission Deadline: July 17, 2006 Author Notification: October 9, 2006 Camera-ready copy due: December 12, 2006 Special Issue publication: First half 2007 ------------------------------------------------------------------------ Date: Mon, 6 Feb 2006 11:15:30 +0100 From: Niels Peek To: ml@isle.org Subject: IDAMAP 2006 Intelligent Data Analysis in Biomedicine And Pharmacology August 25-26, 2006, A two-day workshop in Verona, Italy http://idamap.org/idamap2006 Submission: May 1, 2006 Notification: June 11, 2006 Camera-ready: July 1, 2006 The IDAMAP workshop series is devoted to computational methods for data analysis in medicine, biology and pharmacology that present results of analysis in a form communicable to domain experts that utilizes knowledge of the domain. Typical methods include data visualization, data exploration, machine learning, and data mining. This year's IDAMAP will focus attention on methods for handling temporal data. Topics include, but are not limited to: data mining and machine learning techniques for supervised and unsupervised learning problems; exploiting domain knowledge in learning and data analysis; data visualization and exploration; analysis of large data sets and relational data mining; knowledge management and its integration with intelligent data analysis techniques; and integration of intelligent data analysis techniques within biomedical information systems. Specific attention will be spent on methods for analyzing temporal data, such as: qualitative and quantitative methods for temporal data abstraction; biomedical time series analysis; and analyzing and interpreting longitudinal data. Submitted papers should demonstrate how a select methodology may help solve relevant medical problems and address: the medical or clinical problem being addressed; the availability of prior knowledge; how this knowledge was utilized in the data analysis or interpretation of results; and how the newly discovered knowledge may be utilized. Contributions discussing specific applications of intelligent data analysis techniques are invited, and may cover analysis of medical and health-care data, data from clinical bioinformatics data bases, analysis of pharmacological data, drug design, drug testing, and outcomes analysis. We also invite developers of data analysis tools to submit papers that describe their tool and give a demonstration during the workshop. These papers should describe the underlying methodology of the tool, sketch the potential for application in the field of intelligent data analysis in biomedicine, and describe a case study in which the tool was used. Authors should send an electronic submission in PDF format to both chairs (n.b.peek@amc.uva.nl, carlo.combi@univr.it); please use "IDAMAP SUBMISSION YOUR_NAME" as a subject, where YOUR_NAME is the surname of the first author. Formatting instructions and instructions for authors are on the website. ------------------------------------------------------------------------ Date: Sat, 28 Jan 2006 16:31:47 -0800 From: Miguel Carreira-Perpinan To: ml@isle.org Subject: PhD research assistantships in machine learning at OGI PHD RESEARCH ASSISTANTSHIPS IN ADAPTIVE SYSTEMS AT THE OGI SCHOOL OF SCIENCE AND ENGINEERING AT OHSU Individuals interested in pursuing a PhD in Machine Learning or Computational Neuroscience at OGI are eligible for research assistantships in the Adaptive Systems Laboratory at the OGI School of Science & Engineering (http://adsyl.csee.ogi.edu). The Laboratory, which is part of the Department of Computer Science & Electrical Engineering, carries out research in the areas of machine learning, adaptive signal processing and computational neuroscience. Close ties also exist with the Center for Spoken Language Understanding, the Department of Biomedical Engineering at OGI, the Neurological Sciences Institute, and the OHSU Medical School. One of the four schools of Oregon Health & Science University, OGI is located 12 miles west of Portland, Oregon, in the heart of the Silicon Forest. Portland's extensive high-tech community, diverse cultural amenities and spectacular natural surroundings combine to make the quality of life here extraordinary. To learn more about the department, OGI, OHSU, and Portland, please visit http://www.csee.ogi.edu. Applicants should have a university degree in an area such as computer science, electrical engineering, physics or mathematics, and solid mathematical and programming skills. Background in machine learning, image/speech processing or computer vision is highly desirable. The assistantships cover tuition, a competitive stipend, and travel to research conferences. Students of any nationality may apply. Informal inquiries can be made by sending email (with supporting CV and a statement of research interests) to adsyl-inquiry@csee.ogi.edu or to the appropriate faculty member. For information on submitting a full application to the PhD program in Computer Science, see the OGI admissions information at http://www.ogi.edu/admissions. ------------------------------------------------------------------------ Date: Wed, 8 Feb 2006 9:31:56 PM PST From: Pat Langley To: ml@isle.org Subject: Open position at ISLE The Institute for the Study of Learning and Expertise (ISLE) has an opening for a postdoctoral researcher or masters-level programmer for a new project on learning hierarchical task networks from traces of expert behavior. ISLE is a nonprofit research company based in Palo Alto, California, that has strong ties with Stanford University's Center for the Study of Language and Information. Applicants should have experience with relational approaches to machine learning, such as explanation-based methods or inductive logic programming, as well as an interest in techniques that combine reasoning with learning to acquire complex structures in the presence of background knowledge. Experience of LISP and/or Prolog would be an asset, whereas a commitment to building AI systems and evaluating their behavior on challenging domains is essential. This start date for this position is July 1, 2006. To apply, send electronic mail to Pat Langley . The Web site at http://www.isle.org/ provides information about the Institute's ongoing research activities. ____________________________________ End of ML-LIST Digest Vol 18, No. 2 ************************************