Artificial Neural Networks and Machine Learning – ICANN 2012: 22nd International Conference on Artificial Neural Networks, Lausanne, Switzerland, September 11-14, 2012, Proceedings, Part II

611 Pages·2012·14.51 MB·English

by  Shinya Suzumura

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