Artificial Neural Networks and Machine Learning – ICANN 2012: 22nd International Conference on Artificial Neural Networks, Lausanne, Switzerland, September 11-14, 2012, Proceedings, Part II PDF
Preview Artificial Neural Networks and Machine Learning – ICANN 2012: 22nd International Conference on Artificial Neural Networks, Lausanne, Switzerland, September 11-14, 2012, Proceedings, Part II
Lecture Notes in Computer Science 7553 CommencedPublicationin1973 FoundingandFormerSeriesEditors: GerhardGoos,JurisHartmanis,andJanvanLeeuwen EditorialBoard DavidHutchison LancasterUniversity,UK TakeoKanade CarnegieMellonUniversity,Pittsburgh,PA,USA JosefKittler UniversityofSurrey,Guildford,UK JonM.Kleinberg CornellUniversity,Ithaca,NY,USA AlfredKobsa UniversityofCalifornia,Irvine,CA,USA FriedemannMattern ETHZurich,Switzerland JohnC.Mitchell StanfordUniversity,CA,USA MoniNaor WeizmannInstituteofScience,Rehovot,Israel OscarNierstrasz UniversityofBern,Switzerland C.PanduRangan IndianInstituteofTechnology,Madras,India BernhardSteffen TUDortmundUniversity,Germany MadhuSudan MicrosoftResearch,Cambridge,MA,USA DemetriTerzopoulos UniversityofCalifornia,LosAngeles,CA,USA DougTygar UniversityofCalifornia,Berkeley,CA,USA GerhardWeikum MaxPlanckInstituteforInformatics,Saarbruecken,Germany Alessandro E.P. Villa Włodzisław Duch Péter Érdi Francesco Masulli Günther Palm (Eds.) Artificial Neural Networks and Machine Learning – ICANN 2012 22nd International Conference on Artificial Neural Networks Lausanne, Switzerland, September 11-14, 2012 Proceedings, Part II 1 3 VolumeEditors AlessandroE.P.Villa UniversityofLausanne,NeuroHeuristicResearchGroup 1015Lausanne,Switzerland E-mail:[email protected] WłodzisławDuch NicolausCopernicusUniversity,DepartmentofInformatics 87-100,Torun´,Poland E-mail:[email protected] PéterÉrdi KalamazooCollege,CenterforComplexSystemsStudies Kalamazoo,MI49006,USA E-mail:[email protected] FrancescoMasulli UniversitàdiGenova,DipartimentodiInformaticaeScienzedell’Informazione 16146Genoa,Italy E-mail:[email protected] GüntherPalm UniversitätUlm,InstitutfürNeuroinformatik 89069Ulm,Germany E-mail:[email protected] ISSN0302-9743 e-ISSN1611-3349 ISBN978-3-642-33265-4 e-ISBN978-3-642-33266-1 DOI10.1007/978-3-642-33266-1 SpringerHeidelbergDordrechtLondonNewYork LibraryofCongressControlNumber:2012946038 CRSubjectClassification(1998):I.2,F.1,I.4,I.5,J.3,H.3 LNCSSublibrary:SL1–TheoreticalComputerScienceandGeneralIssues ©Springer-VerlagBerlinHeidelberg2012 Thisworkissubjecttocopyright.Allrightsarereserved,whetherthewholeorpartofthematerialis concerned,specificallytherightsoftranslation,reprinting,re-useofillustrations,recitation,broadcasting, reproductiononmicrofilmsorinanyotherway,andstorageindatabanks.Duplicationofthispublication orpartsthereofispermittedonlyundertheprovisionsoftheGermanCopyrightLawofSeptember9,1965, initscurrentversion,andpermissionforusemustalwaysbeobtainedfromSpringer.Violationsareliable toprosecutionundertheGermanCopyrightLaw. Theuseofgeneraldescriptivenames,registerednames,trademarks,etc.inthispublicationdoesnotimply, evenintheabsenceofaspecificstatement,thatsuchnamesareexemptfromtherelevantprotectivelaws andregulationsandthereforefreeforgeneraluse. Typesetting:Camera-readybyauthor,dataconversionbyScientificPublishingServices,Chennai,India Printedonacid-freepaper SpringerispartofSpringerScience+BusinessMedia(www.springer.com) Preface The InternationalConference onArtificialNeuralNetworks(ICANN) is the an- nual flagship conference of the European Neural Network Society (ENNS). It is the premier European event covering all topics concerned with neural networks and related areas. The aim of ICANN is to bring together researchers from two worlds:informationsciences andneurosciences.The scope is wide, rangingfrom machine learning algorithms to models of real nervous systems. The aim is to facilitate discussions and interactions toward developing more intelligent artifi- cial systems and increasing our understanding of neural and cognitive processes in the brain. The ICANN series of conferences was initiated in 1991 and soon became the major European gathering for experts in these fields. The 22nd International Conference on Artificial Neural Networks (ICANN 2012, http://icann2012.org) washeldon11–14September2012inLausanne,Switzerland,withpre-conference workshopsandsatellitemeetingsonroboticsandconsciousnessstudiesheldon11 September2012.ThehostorganizationistheUniversityofLausanne(UNIL)and itsFacultyofBusinessandEconomics(HEC);thevenueistheInternefBuilding on the UNIL Dorigny Campus on the shore of Lake Geneva. We acknowledge the supportofthe Fondationdu 450`eme,the Soci´et´eAcad´emique Vaudoise,the RectorateofUNIL,the FacultyofBusiness andEconomics,andits Department of Information Systems. The ICANN 2012 organization is non-profit and all financial transactions are checked by the accounting office of UNIL. The 2012 conference is characterized by two major facts: the consolidation of two parallel tracks with a new scheme of reduced fees, and the first ICANN conference without the late John G. Taylor. A variety of topics constituted the focus of paper submissions and it was difficult to categorize the papers either in the brain-inspired computing track or in the machine learning research track. However, after the successful initia- tive of the organizers of ICANN 2011 in Espoo, Finland, to limit the parallel sessions to two, it appeared that a broader audience would follow the oral pre- sentationsifthesameformulawereadoptedin2012.From247paperssubmitted to the conference, the Program Committee and Editorial Board – after a thor- ough peer-review process – selected 162 papers for publication, subdivided in 82 oral presentations in 16 sessions and 80 poster presentations. The quality of the papers received was high and it was not possible to include many papers of good quality in the conference program. Papers selected for oral or poster presentationswereequallygoodandthe attributionto aspecific type ofpresen- tationwasdecided,inthevastmajorityofthecases,accordingtothepreference expressed by the authors. The dual-track, initially intended as brain-inspired computingtrackormachinelearningresearchtrack,simplybecametrackAand track B, because many papers presented an interdisciplinary approach,which is VI Preface in the spirit of ICANN and the goals promoted by ENNS. All posters remained on display during the three days of the conference with a mandatory presenter standingnearoddnumbers onThursday13thandnearevennumbersonFriday 14th. This year the organizers decided to slash the registration fee and focus on the core of ICANN activities at the expense of excluding the lunches. This scheme has proven to be successful and attracted many foreign participants, coming from 35 different countries and all continents, in particular at graduate and postgraduate levels. ThiswasthefirstICANNafterthedeathofProf.JohnGeraldTaylor(JGT), the first president and co-founder of the European Neural Network Society (ENNS).JohnwasborninHayes,Kent,onAugust18,1931.HeobtainedaPhD in Theoretical Physics from Christ’s College, Cambridge (1950–1956),where he was strongly influenced by the teaching of Paul Dirac. John G. Taylor started researchinneuralnetworksin1969andhascontributedtomany,ifnotall,ofits subfields. In 1971 he was appointed to the established Chair in Applied Math- ematics at King’s College London where he founded and directed the Centre forNeuralNetworks.His researchinterests werewide,rangingfromhighenergy physics,superstrings,quantumfieldtheoryandquantumgravity,neuralcompu- tation, neural bases of behavior, and mathematical modelling in neurobiology. After observingthe metal“bending”skills ofUriGellerin1974,Prof.J.G.Tay- lor became interested in parapsychology and sought to establish whether there isanelectromagneticbasisforthephenomenon.Aftercarefulinvestigationchar- acterizedbyaninitialenthusiasmandlateskepticismhecametotheconclusion, expressed in his book Science and the Supernatural (1980), that the paranor- mal cannotbe reconciledwith modern physics.After Francis Crick’shypothesis (1984)ontheinternalattentionalsearchlightroleplayedbythethalamicreticu- lar nucleus, Prof. Taylor became involved in developing a higher cognitive level model of consciousness,using the most recentresults on attentionto describe it as anengineeringcontrolsystem. This led him to the CODAM (attentioncopy) model of consciousness. In 2007, Prof. Taylor developed the first program of its kindinthe hedgefunds industryusingartificialintelligencetechniques tocreate portfolios of hedge funds. He also trained as an actor and performed in plays and films, wrote several science fiction plays, as well as directing stage produc- tions in Oxfordand Cambridge.Throughouthis careerProf.Taylor encouraged young scientists to follow their curiosity in their searchfor a better understand- ing of nature and he served on numerous PhD dissertation juries around the world. This brief biographical sketch of John G. Taylor is not intended to be exhaustivebutitisanattempttopresentanexceptionalperson,thoughhumble and ordinary, yet out of the ordinary,who was part of our community from the very beginning. At the ICANN conferences Prof.Taylorspent much time in the poster sessions interacting with the participants and his presence at the oral sessions was often marked by his questions and comments. The attendants at past ICANN conferences remember that at banquet dinner Prof. Taylorusually gave a short speech that was a condensed summary of his elegance and humor. I had the privilege of his friendship during the past twenty years and I am sure Preface VII that many of us will remember stories about Prof. John Gerald Taylor. Dear John, thank you for your legacy, it is now up to us to pursue your effort, make it grow and flourish. July 2012 Alessandro E.P. Villa John Gerald Taylor (18.VIII.1931-10.III.2012) Organization Committees General Chair Alessandro E.P. Villa Special Sessions Chair Marco Tomassini Tutorials Chair Lorenz Goette Competitions Chair Giacomo Indiveri Program Chairs Wlodek Duch Guenther Palm P´eter E´rdi Alessandro E.P. Villa Francesco Masulli Program Committee and Editorial Board Cesare Alippi Giacomo Indiveri Bruno Apolloni Nikola Kasabov Yoshiyuki Asai Mario Koeppen Lubica Benuskova Stefanos Kollias Roman Borisyuk Petia Koprinkova-Hristova Antoˆnio Braga Irena Koprinska Hans Albert Braun Vera Kurkova J´er´emie Cabessa Giancarlo La Camera Angelo Cangelosi Diego Liberati Angel Caputi Alessandra Lintas Ke Chen Andr´e Longtin Gerard Dreyfus Teresa Ludermir Jean-Pierre Eckmann Thomas Martinetz Marina Fiori Francesco Masulli Jordi Garcia-Ojalvo Maurizio Mattia Philippe Gaussier Claudio Mirasso Michele Giugliano Francesco C. Morabito Tatiana V. Guy Manuel Moreno Arostegui Barbara Hammer Ernst Niebur Ulrich Hoffrage Jose Nunez-Yanez Timo Honkela Klaus Obermeyer Brian I. Hyland Takashi Omori Lazaros Iliadis H´el`ene Paugam-Moisy X Organization Jaako Peltonen Walter Senn Danil Prokhorov Isabella Silkis Barry Richmond Alessandro Sperduti Jean Rouat Marco Tomassini John Rinzel Tatyana Turova Stefan Rotter Roseli Wedemann Stefano Rovetta Stefan Wermter Jorge Santos Additional Reviewers Fabio Babiloni Alfredo Petrosino Simone Bassis Ramin Pichevar Fu¨lo¨p Bazso Marina Resta Francesco Camastra Alessandro Rozza Alessandro Di Nuovo Justus Schwabedal Simona Doboli Vladyslav Shaposhnyk Alessio Ferone Giorgio Valentini Maurizio Filippone Eleni Vasilaki Stefan Heinrich Jan K. Woike Hassan Mahmoud Sean Wood ENNS Travel Grant Committee Wlodzislaw Duch Guenther Palm P´eter E´rdi Alessandro E.P. Villa Secretariat and Publicity Daniela Serracca Fraccalvieri Edy Ceppi Elisabeth Fournier Registration Committee Paulo Monteiro Table of Contents – Part II Multilayer Perceptrons and Kernel Networks (A6) Complex-Valued Multilayer Perceptron Search Utilizing Eigen Vector Descent and Reducibility Mapping ................................. 1 Shinya Suzumura and Ryohei Nakano Theoretical Analysis of Function of Derivative Term in On-Line Gradient Descent Learning........................................ 9 Kazuyuki Hara, Kentaro Katahira, Kazuo Okanoya, and Masato Okada Some Comparisons of Networks with Radial and Kernel Units ......... 17 Vˇera K˚urkova´ Multilayer Perceptron for Label Ranking............................ 25 Geraldina Ribeiro, Wouter Duivesteijn, Carlos Soares, and Arno Knobbe Electricity Load Forecasting: A Weekday-Based Approach............. 33 Irena Koprinska, Mashud Rana, and Vassilios G. Agelidis Training and Learning (C4) Adaptive Exploration Using Stochastic Neurons...................... 42 Michel Tokic and Gu¨nther Palm Comparison of Long-Term Adaptivity for Neural Networks ............ 50 Frank-Florian Steege and Horst-Michael Groß Simplifying ConvNets for Fast Learning............................. 58 Franck Mamalet and Christophe Garcia A Modified Artificial Fish Swarm Algorithm for the Optimization of Extreme Learning Machines..................................... 66 Jo˜ao Fausto Lorenzato de Oliveira and Teresa B. Ludermir Robust Training of Feedforward Neural Networks Using Combined Online/Batch Quasi-Newton Techniques ............................ 74 Hiroshi Ninomiya Estimating a Causal Order among Groups of Variables in Linear Models ......................................................... 84 Doris Entner and Patrik O. Hoyer
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