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Machine Learning List: Volume 17, Number 4 Machine Learning List: Volume 17, Number 4
Tuesday, October 11, 2005 ************************************************************************** Contents New Format for the Machine Learning List Calls for Papers & Participation Special Issue on Applications Eligible for Data Mining Conference on Information Processing and Management of Uncertainty Special Issue on Statistical and Probabilistic Methods for User Modeling Annual Conference of the Cognitive Science Society 19th International FLAIRS Conference Unsupervised Segmentation of Words into Morphemes NIPS 2005 Workshops International Conference on Development and Learning Third International Symposium on Neural Networks 16th International Conference on Automated Planning and Scheduling Intelligent Information Systems PAKDD'06 Call for Tutorial proposals Career Opportunities Postdoctoral Position in Cognitive Models of Learning Postdoctoral Position in Data Mining of Network Formations Research Fellowship in Data Mining/Statistical Process Control Postdoctoral Position in Iterative Control Learning Senior Research Scientist Position at Toyota Technical Center Postdoctoral Positions in Bioinformatics and Neuroimaging Research Faculty Position in AI and Machine Learning Journal Announcements Bayesian Analysis Software Releases VFML library for mining massive data streams YALE 3.0 Closed Loop Simulation System ************************************************************************** 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. ************************************************************************** From: Pat Langley <langley@...> Subject: New Format for the Machine Learning List Date: Mon, 10 Oct 2005 This issue of the Machine Learning List introduces a new format that contains more condensed versions of announcements. This reflects the increased availability of details about meetings, publications, and positions through the World Wide Web, which makes their inclusion here redundant. The new goal of the ML List is to provide readers with brief summaries of these announcements and to point interereted parties to relevant Web pages for more information. We welcome any suggestions for other changes that would let the ML List serve the community better. ------------------------------------------------------------------------- From: Takashi Washio <washio@...> Subject: Special Issue on Applications Eligible for Data Mining Date: Wed, 08 Jun 2005 10:38:46 +0900 Advanced Engineering Informatics Call For Papers of Special Issue on Applications Eligible for Data Mining Deadline of paper submission: 25th, November, 2005 http://www.sciencedirect.com/science/journal/14740346 http://www.elsevier.com/locate/aei A special issue on applications eligible for data mining of Advanced Engineering Informatics will provide clarification of progress and issues in addition to the promotion of wider data mining applications. This special issue seeks papers that discuss useful data mining techniques for various domains, their use of knowledge intensive representations and methods, and that also emphasize significant techniques for future study of data mining. The special issue specially seeks discussion of computer applications that use data mining in support of Engineering. Review Criteria: Due to the mission of this issue, the criteria of paper selection are: (1) significance of applications, (2) essential necessity of data mining, (3) technical presentation that emphasizes informatics and knowledge intensive methods, and (4) readability rather than the technical originality. ------------------------------------------------------------------------- From: Thanh Ha Dang <ThanhHa.Dang@...> Subject: Conference on Information Processing and Management of Uncertainty Date: Tue, 9 Aug 2005 16:50:35 +0200 CALL FOR PAPERS The Eleventh International Conference on Information Processing and Management of Uncertainty (IPMU 2006) Paper submission due date: December 10th, 2005 Web page: http://ipmu2006.lip6.fr The IPMU Conference is organized every two years with the focus of bringing together scientists working on methods for the management of uncertainty and aggregation of information in intelligent systems. This conference provides a medium for the exchange of ideas between theoreticians and practitioners in these and related areas. Topics in theory, methods and tools: Bayesian and Probabilistic Methods, Measure of Information and Uncertainty, Evidence Theory, Possibility Theory, Utility Theory, Measurement Theory, Belief Networks, Chaos Theory, Fuzzy Methods, Rough Sets, Belief Updating, Default Reasoning, Multivalued Logics, Temporal Reasoning, Non-standard Logics, Non-monotonic Logics, Approximate Reasoning, Knowledge Acquisition, Knowledge Representation, Uncertainty in Cognition, Information Incompleteness and Inconsistency, Genetic Algorithms, Evolutionary Computation, Machine Learning, Inductive Methods, Neural Networks, Aggregation Methods, Data Analysis. Topics in application fields: Intelligent Systems, Fuzzy Control, Diagnosis Systems, Expert Systems, Hybrid Systems, Clustering, Databases, Classification, Image Processing, Intelligent Agents, Pattern Recognition, Medical Applications, Bioinformatics, Financial Engineering, Multi-Media Management, Decision Support Systems, Dedicated Architectures and Software, Software engineering, Multicriteria and Group Decision Making, Information systems, Information Retrieval, Information Fusion, Semantic Web, Data Mining, Cyber Security. -------------------------------------------------------------------------- From: Ingrid Zukerman <Ingrid.Zukerman@...> Subject: Special Issue on Statistical and Probabilistic Methods for User Modeling Date: Sun, 21 Aug 2005 22:47:39 +1000 User Modeling and User-Adapted Interaction Special Issue on Statistical and Probabilistic Methods for User Modeling Submission Deadline is Oct. 31, 2005 http://www.umuai.org/news_on_journal.html This Special Issue of User Modeling and User-Adapted Interaction will explore recent developments in different aspects of statistical and probabilistic techniques for user modeling. Contributions are particularly welcome in, but not limited to, the following areas: - user modeling applications of machine learning and statistical techniques, such as Bayesian networks, decision trees and graphs, clustering techniques, decision-theoretic approaches, and neural networks. - theoretical developments in statistical modeling and machine learning relevant to user modeling issues. - methods for the statistical evaluation of user models. - adaptations of user models over time (including cold start and concept drift). - combination of content-based and collaborative user models. - learning statistical user models from data sets with different characteristics, e.g., imbalanced data sets, very large data sets, and synthetic data sets. -------------------------------------------------------------------------- From: Ron Sun <rsun@...> Subject: Annual Conference of the Cognitive Science Society Date: Fri, 26 Aug 2005 09:49:21 -0400 CogSci 2006 The Twenty-Eighth Annual Conference of the Cognitive Science Society Paper Submissions due: February 1, 2006 http://www.cogsci.rpi.edu/~rsun/cogsci2006/ We invite submissions to the Twenty-Eighth Annual Conference of the Cognitive Science Society, the premier conference 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. Plenary speakers will include: 1. Robert Siegler (CMU) 2. Daniel Schacter (Harvard) 3. Roger Shepard (Stanford) Invited symposia will provide more explorations of the topics: 1. The Synergy between Implicit and Explicit Learning Processes 2. The Emerging Learning Sciences -------------------------------------------------------------------------- From: FLAIRS 2006 <flairs06@...> Subject: 19th International FLAIRS Conference Date: Sun, 28 Aug 2005 22:57:56 -0500 (EST) FLAIRS 2006 Melbourne Beach, USA http://www.indiana.edu/~flairs06 11th-13th May 2006 Submission of papers 21st Nov 2005 The 19th International FLAIRS Conference will be held 11th-13th May 2006, at the Crowne Plaza - Melbourne Oceanfront, Melbourne Beach, Florida, USA. Melbourne Beach is on the ocean front in the City of Melbourne, on Florida's "Space Coast" centered around NASA's Kennedy Space Center, and with easy access to Orlando and the Disney World attractions. The conference will feature technical papers, special tracks, and invited speakers. We are planning a conference reception at the Florida Institute of Technology, and a conference excursion to the Kennedy Space Center. The following special tracks have been accepted at FLAIRS 2006. + Artificial Intelligence Education + Artificial Intelligence in Music and Art + Case-Based Reasoning + Evaluation and Refinement of Intelligent Systems + Evolutionary Optimization + Intelligent Distributed Sensor Networks + Intelligent Tutoring Systems + Machine Learning + Modeling the Real World through Contexts + Natural Language and Knowledge Representation + Neural Networks + Secure Multiparty Computations and Distributed Constraint Reasoning + Spatio-Temporal Reasoning + Automatic Annotation by Categories for Text Information Extraction + Trends in Basic and Applied Natural Language Processing + Uncertain Reasoning Links to the respective special track pages can be found at: http://www.indiana.edu/~flairs06/st.html Please contact the respective track organizers for further details. -------------------------------------------------------------------------- From: Mikko Kurimo <mikkok@...> Subject: Unsupervised Segmentation of Words into Morphemes Date: Wed, 31 Aug 2005 13:58:12 +0300 Unsupervised segmentation of words into morphemes -- Challenge 2005 Deadline for submission of segmentations: 15 January 2006 http://www.cis.hut.fi/morphochallenge2005/ Part of the EU Network of Excellence PASCAL Challenge Program. Participation is open to all. The objective of the Challenge is to design a statistical machine learning algorithm that segments words into the smallest meaning- bearing units of language, morphemes. Ideally, these are basic vocabulary units suitable for different tasks, such as text understanding, machine translation, information retrieval, and statistical language modeling. The scientific goals are: * To learn of the phenomena underlying word construction in natural languages * To discover approaches suitable for a wide range of languages * To advance machine learning methodology The results will be presented in a workshop arranged in connection with other PASCAL challenges on machine learning. -------------------------------------------------------------------------- From: Samuel Kaski <samuel.kaski@...>, Shivani Agarwal <shivani@...>, William Noble <noble@...>, Daniel Silver <danny.silver@...> Subject: NIPS 2005 Workshops Workshop on Machine Learning for Implicit Feedback and User Modeling Deadline for papers: October 21 http://www.cis.hut.fi/inips2005/ Inferring Relevance from Eye Movements Challenge 2005 Deadline for papers: October 21 http://www.cis.hut.fi/eyechallenge2005/ Workshop on Learning to Rank Deadline for papers: October 21 http://web.mit.edu/shivani/www/Ranking-NIPS-05/ Workshop on Learning from Heterogeneous Data Extended abstract due by November 1, 2005. Neural Information Processing Systems http://noble.gs.washington.edu/hdata Workshop on Inductive Transfer: Ten Years Later Deadline for papers: October 21 http://iitrl.acadiau.ca/itws05/ -------------------------------------------------------------------------- From: Mike Gasser <mikegasser@...> Subject: International Conference on Development and Learning Date: Mon, 5 Sep 2005 10:53:46 -0500 ICDL 2006: International Conference on Development and Learning Paper Submission Deadline: Feb. 6, 2006 http://www.icdl06.org The theme of this years conference centers on development as a process of dynamic change that occurs within a complex and embodied system. The dynamics of development extend across multiple levels, from neural circuits, to changes in body morphology, sensors, movement, behavior, and inter-personal and social patterns. The goal of the conference is to present state-of-the-art research on autonomous development in humans, animals and robots, and to continue to identify new interdisciplinary research directions for the future of the field. Paper submissions (for details regarding format and submission/review process see our website at http://www.icdl06.org) are invited on: General Principles of Development and Learning in Humans and Robots Neural, Behavioral and Computational Plasticity Embodied Cognition: Foundations and Applications Social Development in Humans and Robots Language Development of Learning Dynamic Systems Approaches Emergence of Structures through Development Development of Perceptual and Motor Systems Models of Developmental Disorders -------------------------------------------------------------------------- From: ISNN2006 <ISNN2006@...> Subject: Third International Symposium on Neural Networks Date: Wed, 7 Sep 2005 14:33:48 +0800 Third International Symposium on Neural Networks hSpecial session proposal (ISNN2006): November 1, 2005 Paper submission (ISNN2006): November 15, 2005 ttp://www.acae.cuhk.edu.hk/~isnn2006 http://cilab.uestc.edu.cn/isnn2006 Prospective authors are invited to submit full-length papers (6 pages normally and 10 pages maximum) by the submission deadline. Potential organizers are also invited to enlist five or more papers with cohesive topics to form special sessions. The submission of a paper implies that the paper is original and has not been submitted under review or copyright protected elsewhere and will be presented by an author if accepted. All submitted papers will be refereed by experts in the field based on the criteria of originality, significance, quality, and clarity. ISNN2006 has teamed up with the International Journal of Neural Systems, one of the distinguished journals on neural networks, for publishing a Special Issue on Advances in Neural Networks. All submitted papers will have opportunities for consideration for this Special Issue. The selection will be carried out during the review process as well as at the conference presentation stage. The Editor-in-Chief of IJNS and the guest editors of the Special Issues will make decisions on submitted papers based referees' comments and recommendations, as well as quality and presentation of the papers, and select around twenty five papers. -------------------------------------------------------------------------- From: Hector Munoz-Avilla <hem4@...> Subject: International Conference on Automated Planning and Scheduling Date: Sun, 11 Sep 2005 00:50:54 -0400 CALL FOR PAPERS The 16th International Conference on Automated Planning and Scheduling Abstract Submission Deadline: November 11, 2005 Paper Submission Deadline: November 14, 2005 http://icaps06.icaps-conference.org/ The International Conference on Automated Planning and Scheduling is the premier forum for researchers and practitioners in intelligent planning and scheduling and related fields. Topics of relevance to the conference include planning and scheduling theory and practice, as well as applications of planning and scheduling technology to challenging problem domains. The organizing committee solicits paper submissions on all aspects of planning and scheduling, including but not limited to the topics listed at the conference web site. Submissions that link planning and scheduling to the related fields of constraint reasoning, operations research, search, uncertainty reasoning, and verification and validation are strongly encouraged. -------------------------------------------------------------------------- To: IIS:IIPWM'06 Conference <iipwm@...> Subject: Intelligent Information Systems Date: Wed, 14 Sep 2005 13:48:17 +0200 INTELLIGENT INFORMATION SYSTEMS 2006 - IIS'06 New Trends in Intelligent Information Processing and Web Mining Submission Deadline: November 7, 2005 Conference Web page: http://iipwm.ipipan.waw.pl Papers on these and related subjects are particularly encouraged: * Artificial Immune Systems, * Search Engines, * Computational Linguistics, * Knowledge Discovery. The Conference's focus will also be on the following topics: * new computing paradigms * advanced data analysis, * new machine learning paradigms, * reasoning technologies, * natural language processing, * novelty detection, * new optimization technologies, * applied data mining using statistical and non-standard approaches, * technologies for very large text bases, * uncertainty management. -------------------------------------------------------------------------- From: Osmar Zaiane <zaiane@...> Subject: PAKDD'06 Call for Tutorial proposals Date: Mon, 19 Sep 2005 01:28:11 -0600 CALL FOR TUTORIAL PROPOSAL: PAKDD 2006 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining Submission Deadline: October 31, 2005 http://www.ntu.edu.sg/sce/pakdd2006/ The PAKDD series of conferences is an established and prestigious forum for the exchange of the latest research results in data mining. Held annually at attractive Australasian cities, the conference provides unique opportunities for data mining researchers, practitioners, developers, and users to explore new ideas, techniques, and tools, and to exchange experiences. The previous events were held in Singapore, Melbourne, Beijing, Kyoto, Hong Kong, Taipei, Seoul, Sydney, and Hanoi. PAKDD 2006 will be once again held in Singapore. An integral part of PAKDD 2006 is the tutorial program. Presenters are invited to submit proposals for tutorials in all areas of data mining. Tutorials will typically be either full-day (6 hrs) or half-day (3 hrs). -------------------------------------------------------------------------- From: Ron Sun <rsun@...> Subject: Postdoctoral Position in Cognitive Models of Learning Date: Fri, 10 Jun 2005 14:11:54 -0400 I am looking for a postdoctoral researcher, to join in a basic research project investigating cognitive modeling, cognitive architectures, and human skill learning. The starting date is September 1, 2005 (although a slight delay, say by a couple of months, is also possible). This will be a full-time research position, with the expectation that you devote all your time to project-related research work (not your own research topics). Prospective applicants should have a finished Ph.D degree before starting, by September 1, 2005 (or shortly thereafter). They should have strong backgrounds in computer science (the equivalent of a BS in computer science), with strong Java programming skills, and have prior exposure to psychology and cognitive science (with background in human and machine learning, motivation, and meta-cognition preferred), and other related areas. Prospective applicants with interests in cognitive science should apply by emailing: (1) a complete vitae, and (2) samples of best prior writings (especially published papers), and also FAX (3) GRE/TOEFL scores if available, and other pertinent information. Make sure to also FAX (4) copies of all transcripts of all BS, MS, Ph.D programs previously attended. Also FAX (5) reference letters if available. To find out more about my own research, please see the Web page at: http://www.cogsci.rpi.edu/~rsun Apply as soon as possible. Completed applications will be considered as they come in, until the position is filled. Professor Ron Sun Cognitive Science Department Rensselaer Polytechnic Institute -------------------------------------------------------------------------- From: Hussein Abbass <h.abbass@...> Subject: Postdoctoral Position in Data Mining of Network Formations Date: Mon, 4 Jul 2005 11:42:56 +1000 University of New South Wales, School of Information Technology and Electrical Engineering, Canberra, Australia. The School of Information Technology and Electrical Engineering, the University of New South Wales (UNSW) at the Australian Defence Force Academy, Canberra, Australia, is pleased to advertise for a Post-Doctoral Fellow Position in the area of Data Mining of Network Formations. UNSW is one of the top research universities in Australia. The appointment will be a fixed-term of 1 year. The successful candidate will work on developing data mining algorithms for the identification of social network structures from a stream of data. The successful applicant will join an active research group of PhD students and post-docs and will work jointly with the Artificial Life and Adaptive Robotics Laboratory (http://www.itee.adfa.edu.au/~alar/) and the Virtual Environment and Simulation Laboratory (http://www.itee.adfa.edu.au/research/vesl/). The successful candidate should have, or have submitted, a PhD in computer science, applied mathematics or a closely related field. The candidate is expected to be knowledgeable in one or more of: social networks, network sampling, graph theory, machine learning, and statistical inference. Knowledge and understanding of equity and diversity principles and OHS practices is essential. Knowledge of JAVA or C++ is desirable for this appointment. The first screening of applicants will occur on the 10th of July 2005. The position will remain open until filled. Inquiries regarding the appointment and expression of interest should be directed to Dr Hussein Abbass at abbass@.... -------------------------------------------------------------------------- From: Sean McLoone <s.mcloone@...> Subject: Research Fellowship in Data Mining/Statistical Process Control Date: Mon, 4 Jul 2005 14:53:32 -0500 The Department of Electronic Engineering, National University of Ireland Maynooth invite applications for a PhD research project in Data Mining/ Statistical Process Control funded by (and in collaboration with) Intel Ireland Ltd. This research project will focus on the development of algorithms for data mining applications focusing on parametric process data sets to facilitate knowledge discovery on data through a variety of data refinement processes which makes the information optimally useful for data visualization, statistical process control and scheduling of maintenance. The research will focus on data sets generated by process tools used by Intel in their 200 and 300mm semiconductor manufacturing facilitates located at Leixlip, Co. Kildare. The work will use a variety of techniques in the mathematical and control systems sciences. Candidates should be well qualified (ideally 1st Hons) with a background in mathematics, electronic engineering or a cognate discipline. Any experience in data modeling, data mining or statistical process control would be an advantage. The successful candidate will be required to spend a significant amount of time at Intel's Leixlip site working with engineers from Intel's process engineering and IT departments, so any demonstrated ability to work successfully in a large company environment (e.g. through successful completion of a work placement program, or previous employment) would be beneficial. The successful candidate will register for a PhD at NUI Maynooth Project duration: 3 years Funding level: 20,000 euro per annum (to include fees and all expenses) Contact: Dr. Sean McLoone (sean.mcloone@...) or Prof. John Ringwood (john.ringwood@...) -------------------------------------------------------------------------- From: A. Tayebi <tayebi@...> Subject: Postdoctoral Position in Iterative Control Learning Date: Fri, 5 Aug 2005 00:18:04 -0500 A postdoctoral position in nonlinear control theory and iterative learning control is available in the department of Electrical Engineering, Lakehead University, Ontario, Canada. Interested candidates are encouraged to send their CV with a complete list of publications along with the names and e-mail addresses of three references to kromito@.... -------------------------------------------------------------------------- From: Debra Adams <dadams@...> Subject: Senior Research Scientist Position at Toyota Technical Center Date: Sat, 3 Sep 2005 05:37:30 -0500 Toyota Technical Center (TTC) is Toyota's largest engineering and research organization in North America, located in Ann Arbor, MI. TTC is seeking an exceptional individual for the full-time position of Senior Research Scientist in the intersection of Computational Intelligence and Robotics research activities, to become a member of the Technical Research Department. TTC prefers a researcher with experience in sensor fusion for automotive and robotic systems. This position will offer opportunities for collaboration with leading North American and global research institutions. The candidate should also have experience in mentoring junior researchers and have some research project management experience. This research is intended to break new ground and advance the state of the art. Job Duties and Responsibilities: Apply special knowledge and talents to develop and execute new, independent research projects for automotive and robotic applications Provide guidance to on-site researchers and research assistants Interact with world renowned and leading researchers in applicable areas Host visiting Toyota engineers and scientists Provide deliverables such as written and oral reports, as well as publications for peer-reviewed journals and conferences. Qualifications: Experience in Artificial Intelligence, intelligent signal processing and sensor-fusion research Experience in automotive safety systems is preferred Experience in robotic research and testing Experience in mentoring junior researchers Experience in research project management Familiarity with computational intelligence is preferred (e.g., neural networks, fuzzy logic, evolutionary algorithms, data mining) Ph.D. or Sc.D. in a related field of study Good written and oral communication skills Ability to work well with others in a team environment A willingness to travel Position is located in Ann Arbor, MI. Please apply online to Toyota using the following URL (preferred way to apply): http://tmm.recruitsoft.com/servlets/CareerSection?art_ip_action=FlowDispatcher&flowTypeNo=13&pageSeq=2&reqNo=25222&art_servlet_language=en&csNo=10103 or via e-mail to Debra Adams, dadams@... -------------------------------------------------------------------------- From: Terran Lane <terran@...> Subject: Postdoctoral Positions in Bioinformatics and Neuroimaging Date: Wed, 14 Sep 2005 09:59:42 -0600 The machine learning research group at the University of New Mexico has openings for two postdoctoral researchers. The first position is in kernel, Bayesian, and/or relational methods with applications to Bioinformatics. The second position is in Bayesian, relational, and/or spectral graph methods for analysis of functional neuroimaging data. The first position will last up to a year, with the possibility of renewal thereafter; the second position can last up to three years. For more information, including the complete position descriptions and application information, please go to http://www.cs.unm.edu/~terran/ and follow the links under Postdoctoral Research Positions. -------------------------------------------------------------------------- From: Robert Holte <holte@...> Subject: Research Faculty Position in AI and Machine Learning Date: Fri, 30 Sep 2005 09:22:59 -0600 (MDT) The Department of Computing Science at the University of Alberta is seeking a qualified individual to fill a position at the level of assistant or associate professor in the area of artificial intelligence (www.cs.ualberta.ca). This is a soft-funded tenure track position. The initial appointment will be for three years, and continuation is subject to availability of funding. The successful candidate will be working with the Alberta Ingenuity Centre for Machine Learning. Candidates should have a Ph.D. in Computing Science or equivalent, with specialization in artificial intelligence. Preference will be given to applicants with knowledge and experience in machine learning, with an emphasis on reinforcement learning. The candidate is expected to establish their own research program, supervise graduate students, and teach at both the graduate and undergraduate level. The Department highly values curiosity-driven research. Strong communication skills, project management, inter-personal skills, and team leadership are important qualities. -------------------------------------------------------------------------- From: ba-edast@... Subject: Bayesian Analysis Date: Mon Aug 8 09:44:25 2005 The first issue of the new electronic journal Bayesian Analysis has been published at http://ba.stat.cmu.edu. The first issue includes the articles: S. Fienberg, When Did Bayesian Inference Become `Bayesian'? A. Gelfand, J. Silander, S. Wu, A. Latimer, P. Lewis, A. Rebelo, and M. Holder, Explaining Species Distribution Patterns Through Hierarchical Modeling, with commentary by J. Hoeting and J. VerHoef. L. House, M. Clyde and Y. Huang, Bayesian Identification of Differential Gene Expression Induced by Metals in Human Bronchial Epithelial Cells. D. Blei and M. Jordan, Variational inference for Dirichlet process mixtures. C. Holmes and L. Held, Bayesian auxiliary variable models for binary and multinomial regression. J. Andrade and A. O'Hagan, Bayesian robustness modelling using regularly varying distributions. The journal is sponsored by the International Society for Bayesian Analysis. -------------------------------------------------------------------------- From: Pedro Domingos <pedrod@...> Subject: VFML library for mining massive data streams Date: Wed, 18 May 2005 22:55:46 -0700 The VFML (Very Fast Machine Learning) library for mining very large databases and data streams is now available at http://www.cs.washington.edu/dm/vfml/ It is written in C, and includes highly scalable implementations of several widely used machine learning algorithms: * VFDT: Decision tree induction * CVFDT: Decision tree induction with concept drift * VFBN: Bayesian network structure learner * VFEM: EM algorithm for mixtures of Gaussians * VFKM: K-means clustering * Etc. In addition, VFML includes tools for data preparation, testing, and rapid development of stream mining systems. -------------------------------------------------------------------------- From: Ingo Mierswa <ingo.mierswa@...> Subject: Yale 3.0 Date: Mon, 18 Jul 2005 17:48:43 +0200 Introducing the new version 3.0 of YALE (Yet Another Learning Environment): http://yale.cs.uni-dortmund.de The new version includes a huge number of major improvements. Some of them are listed below, the complete list of changes can be found at: http://sourceforge.net/project/shownotes.php?release_id=341383 YALE provides more than 200 operators for data mining and machine learning and allows the design of complex process chains/trees. The well known machine learning library Weka is also fully integrated. YALE is a freely available open source software under the terms of the GNU General Public License. Since YALE is entirely written in Java, it runs on any major platform/operating system. You are welcome to use it! -------------------------------------------------------------------------- From: Martin Riedmiller <Martin.Riedmiller@...> Subject: Closed Loop Simulation System Date: Mon, 19 Sep 2005 14:47:47 +0200 A new release of CLSquare (closed loop simulation system) is ready for free download at http://amy.informatik.uni-osnabrueck.de/clsquare CLSquare simulates a control loop for closed loop control. Although originally designed for training and testing Reinforcement Learning controllers, it also applies to other learning and non-learning controller concepts. Currently available plants: Acrobot, bicycle, cart pole, cart double pole, pole, mountain car, maze. Currently available controllers: linear controller, Reinforcement learning Q table, neural network based Q controller. It comes with many useful features, e.g. graphical display and statistics output, documentation, and many demos for quick starting. ------------------------------------ End of ML-LIST Digest Vol 17, No. 4 ************************************ |
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