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Autonomous Machine Learning (AML) Section I am pleased to announce that Autonomous Machine Learning (AML) SIG is the first SIG to be elevated to a Section within INNS. Being a Section has the following benefits:
Being a Section also comes with additional obligations as specified by the BOG:
We currently have a number of volunteers helping out with AML Section affairs, most notably Prof. Nistor Grozavu of Institut Galilée, Paris 13 University, France, and Prof. Nils T Siebel of HTW University of Applied Sciences Berlin, Germany. But we need to get better organized and create a committee to handle our expanded set of activities. Please let me know ([email protected]) if you want to volunteer for next year (2012). We can have elections next year (2012) once INNS members sign up for the AML Section. Again, we hope more INNS members will join the AML Section this year and be part of the worldwide effort to create widely deployable learning systems. Motivation for AML Section Much of the justification for creating this SIG (now a Section) is derived from the report of a US National Science Foundation (NSF) workshop in July, 2007 on “Future Challenges for the Science and Engineering of Learning.” Here is the summary of the “Open Questions in Both Biological and Machine Learning” from the workshop (http://www.cnl.salk.edu/Media/NSFWorkshopReport.v4.pdf). “Biological learners have the ability to learn autonomously, in an ever changing and uncertain world. This property includes the ability to generate their own supervision, select the most informative training samples, produce their own loss function, and evaluate their own performance. More importantly, it appears that biological learners can effectively produce appropriate internal representations for composable percepts -- a kind of organizational scaffold - - as part of the learning process. By contrast, virtually all current approaches to machine learning typically require a human supervisor to design the learning architecture, select the training examples, design the form of the representation of the training examples, choose the learning algorithm, set the learning parameters, decide when to stop learning, and choose the way in which the performance of the learning algorithm is evaluated. This strong dependence on human supervision is greatly retarding the development and ubiquitous deployment autonomous artificial learning systems. Although we are beginning to understand some of the learning systems used by brains, many aspects of autonomous learning have not yet been identified.” We believe INNS and the neural network community at large has a special obligation to step up to this challenge of creating autonomous learning systems that do not depend on human supervision. INNS approved the formation of AML SIG in April 2009 and our membership has grown since then. Our current mailing list has more than 225 members worldwide and its growing. AML Section Objectives The objectives of this Section are to:
We hope more INNS members will join the AML Section this year and be part of the worldwide effort to create widely deployable learning systems. AML Section Website We currently have a website that is under construction by Prof. Nistor Grozavu of Institut Galilée, Paris 13 University, France. We would like to expand this website to post information about various research activities of our members, job openings, papers and other special events. INNS SIG/RIG and Conference ReportsVol.1, No.1, October 2011 35 Natural Intelligence: the INNS Magazine AML Section Mail-server The mail-server for the AML SIG (now a Section) and its various specialized discussion lists is maintained by Prof. Nils T Siebel of HTW University of Applied Sciences Berlin, Germany. You can subscribe and unsubscribe to/from the AML SIG mailing list through the website http://erlars.org/mailman/listinfo/aml-sig_erlars.org. If you want to post to everyone all you need to do is send an email to [email protected]. Messages are moderated to keep the number of messages and their relevancy to the list subject in check. AML Section Discussion Groups One discussion this summer was about newly discovered concept cells in the human brain and it continued for nearly two months. The concept cells were discovered by of a group of neuroscientists at UCLA (University of California, Los Angeles, USA) under the leadership of Prof. Itzhak Fried and Caltech (California Institute of Technology, Pasadena, CA, USA) under the leadership of Prof. Christof Koch. Participants in this discussion included Profs. Fried and Koch and their co-authors. There is an article titled “Discovery of concept cells in the human brain – Could it change our science?” in this first issue of Natural Intelligence. We invited Dr. Moran Cerf from the UCLA/Caltech group to give a talk on concept cells and the various experiments with epilepsy patients at our AML SIG annual meeting in San Jose during IJCNN 2011. It turned out to be one of the most interesting and informative talks at IJCCN 2011. These discussions have indeed been very productive in clarifying theoretical issues and ideas. So we hope to continue discussions of this nature within our mailing list. And we try to bring the best experts in the field to join these discussions. So this could turn out to be of tremendous help to the challenging research we are engaged in. AML Section Committee We currently have a number of volunteers helping out with AML Section affairs, most notably Prof. Nistor Grozavu of Institut Galilée, Paris 13 University, France, and Prof. Nils T Siebel of HTW University of Applied Sciences Berlin, Germany. But we need to be better organized and create a committee to handle our expanded set of activities. We have some volunteers but need more. Please let me know ([email protected]) if you want to volunteer for next year (2012). We can hold elections next year (2012) once INNS members sign up for the AML Section. Again, we hope more INNS members will join the AML Section this year and be part of the worldwide effort to create widely deployable learning systems. AML Sessions, Panels and Workshops at Conferences Join the Autonomous Machine Learning Section TODAY!
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