2003 International Joint Conference on Neural Networks

SUMMARY OF SPECIAL SESSIONS:

Chairs - Titles
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Csaba Rekeczky and Tamas Roska - Cellular visual microprocessors:
Toporgraphic array computing on data flows.
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Steve Grossberg - Visual cortex: How illusions represent reality
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Robi Polikar - Incremental Learning
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Andreas A. Ioannides and John G. Taylor - Attention and Consciousness in
Normal Brains: Theoretical models and phenomenological data from
Magnetoencephalography (MEG).
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Mitra Basu -  Biologically inspired/motivated computational models
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Jim DeLeo and Roberto Tagliaferri - Patient Care and Clinical Decision
Support.
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F. Carlo Morabito and Sameer Antani - Knowledge Discovery, and Image and
Signal Processing in Medicine.
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Francesco Masulli and Larry Reeker - Bioinformatics.
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Eduardo Bayro-Corrochano - Geometric Neurocomputing.
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Robert J. Marks and John Vian - Applications in Aerospace.
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Robert Kozma, Ali Minai and DeLiang Wang - Dynamical Aspects of 
Information Encoding in Neural Networks.
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SPECIAL SESSION PROGRAMS:

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Warren Fox and Mohamed El-Sharkawi:
Applications in Underwater Acoustics

Jae-Byung Jung,James H. Jacob, and Gerald F. Denny, Patrick K. Simpson,
"Broadband Sonar Target Classification: Pool Experiments."

Benjamin B. Thompson, Robert J. Marks II, Mohamed A. El-Sharkawi, R.T.
Miyamoto, W. J. Fox, C.J. Eggen, G. M. Anderson & M. Hazen,
"Inversion of Neural Network Underwater Acoustic Model for Acquisition of
Bottom Parameters Using a Modified Particle Swarm Optimizer."

Ram Balasubramanian, R.J. Marks II, M.A. El-Sharkawi, J.B. Jung, R.T.
Miyamoto, G.M. Andersen, C.J. Eggen & W.J. Fox,
"Self-Selective Clustering of Data Training Data Using the Maximally-
Receptive Classifier/Regression Bank."

Tobias Mann, Robert J. Marks II, Mohamed A. El-Sharkawi, R.T. Miyamoto, W.
J. Fox, C.J. Eggen, G. M. Anderson & M. Hazen,
"High Dimensional RegressionAnalysis of Multilayer Neural Networks Applied
to Underwater acoustics"

Jae-Byung Jung,James H. Jacobs, George A. Dowding, Patrick K. Simpson,
"Initial Species Discrimination Experiments with Riverine Salmonids."

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Csaba Rekeczky and Tamas Roska - Cellular visual microprocessors:
Toporgraphic array computing on data flows.

Design and Synthesis Methods for Cellular Neural Networks
M. Gilli, P. P. Civallieri, and F. Corinto, Department of Electronics,
Polytechnic of Turin

A New Structure of Large-Neighborhood Cellular Nonlinear Network (LN-CNN)
Chiu-Hung Cheng, Sheng-Hao Chen, Li-Ju Lin, Kuan-Hsun Huang, Chung-Yu Wu,
and Tamas Roska

Nanoelectronics and Giga-scale Systems Lab, National Chiao Tung University

Cortically-inspired Visual Processing with Higher Order CNNs,
B. E. Shi, Department of Electrical and Electronic Engineering, Hong Kong
University of Science and Technology

High Speed Cellular Array Computer Realizations for Low Power Applications.
A. Paasio, M. Laiho, A. Kananen, and K. Halonen, Electronic Circuit Design
Laboratory, Helsinki University of Technology

Feature Guided Visual Attention with Topographic Array Processing and
Neural Network-based Classification.
G. Timar, B. David, I. Szatmari, and Cs. Rekeczky, Analogical and Neural
Computing Systems Laboratory, Computer and Automation Institute, Hungarian
Academy of Sciences

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Stephen Grossberg - Visual cortex: How illusions represent reality

Perceptual processes that create objects from fragments
Philip Kellman, UCLA

Cortical dynamics of form perception
Stephen Grossberg, Boston University

Moving in a fog:  How contrast affects seen movement
Stuart Anstis, UCSD

Cortical dynamics of motion integration and segmentation
Ennio Mingolla, Boston University

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Robi Polikar - Incremental Learning

Competitive Learning Mechanisms for Scalable,
Incremental and Balanced Clustering of Streaming Texts
Joydeep Ghosh, University of Texas, Austin, TX

Rule Learning with Partial Instance Memory for Changing Concepts
Mark Maloof, Georgetown University, Washington D.C.

Formal models of incremental learning and their analysis
Steffen Lange, German Research Center for Artificial Intelligence,
Saarbrücken, Germany

Ensemble of Classifiers Based Incremental Learning with Dynamic
Voting Weight Update
Robi Polikar, Stefan Krause and Lyndsay Burd, Rowan University, Glassboro,
NJ

Efficient Incremental SVM Learning and Cross-Validation
Chris Diehl and Gert Cauwenberghs, Johns Hopkins University, Baltimore, MD

An experimental study of semi-supervised learning in exemplar-based
classifiers
G. Anagnostopoulos, M. Bharadwaj and M. Georgiopoulos, Univ. of Central
Florida, Orlando, FL

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Andreas A. Ioannides and John G. Taylor - Attention and Consciousness in
Normal Brains: Theoretical models and phenomenological data from
Magnetoencephalography (MEG).

The CODAM Control Model of Attention & Consciousness.
JG Taylor, Kings College London, UK

Testing models of attention with MEG.
AA Ioannides & JG Taylor, Kings College London, UK

Early brain activity related to attention and emotion recognition in choice
reaction and face processing protocols.
LC Liu, V Poghosyan  & AA Ioannides, RIKEN BSI, Saitama, Tokyo

Modeling oritofrontal involvement in decision making on a gambling task
D Levine  University of Texas at Arlington

Simulations of Attention Control Models in Sensory and Motor Paradigms
JG Taylor & N Fragopanagos, Kings College London, UK

Conciousness and its correlates in awake condition, in different sleep
stages and in epilepsy.
PBC Fenwick, GK Kostopoulos, LC Liu & AA Ioannides, RIKEN BSI, Saitama,
Tokyo


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Mitra Basu -  Biologically inspired/motivated computational models.

Panel discussion with four people:
Dr. Jon Timmis,
Computing Laboratory, University of Kent at Canterbury,

Dipankar Dasgupta
Department of Computer Science
The University of Memphis

Daniel D. Lee, Ph.D.
Dept. of Electrical Engineering and Bioengineering
University of Pennsylvania

Guang R. Gao
Professor of Electrical and Computer Engineering
University of Delaware

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Jim DeLeo and Roberto Tagliaferri - Patient Care and Clinical Decision
Support.

Comparison and Hybridization of Neural Networks and Fuzzy Logic in
Biomedical Applications,
A. O'Brien

Survival Analysis and Neural Networks
A. Eleuteri, R. Tagliaferri, L. Milano, S. De Placido, M. De Laurentiis

Modelling Cancer Cellular Population with Neural Networks
R.Tagliaferri, A. Volpicelli, N. Di Simone, S. De Placido, M. De Laurentiis

Neural Network Ensembling for Confidence:  Predicting Analyte Values from
Other
Same Specimen Analyte Values in the Clinical Laboratory
J. DeLeo,  A. Remaley, S. Rosenfeld

Finding Patient Cluster Attributes Using Auto-Associative ANN Modelling,
Z. Boger

Application of probabilistic neural networks to population pharmacokinetics,
E. Pasero, M. Costa, M. Eandi

Multi-Layer Perceptron versus Probabilistic Neural Networks in Medical
Diagnosis:
Differential Diagnosis of Mammary Tumours
A.G. Floares, L. Lazar


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Carlo Morabito and Sameer Antani - Knowledge Discovery, and Image and Signal
Processing in Medicine.

A Neural Network Classifier for Lung Nodule Detection
P. Campadelli , E. Casiraghi

Vertebra Shape Classification for Content-Based Image Retrieval
S. Antani, L. R. Long, R. J. Stanley, G. R. Thoma

Knowledge Discovery in Support of Early Diagnosis of  Hepatocelluar
Carcinoma  
F. Ciochetta, R. Dell'Anna, F. Demichelis, A. P. Dhillon, A. Quaglia, A.
Shoner

A SVM Classification Scheme for Electro-Myographic Data
F.C. Morabito

Adaptive Neural Networks Control of Drug Dosage Regimens in Cancer
Chemotherapy
A. G. Floares, Carmen Floares, M. Cucu, L. Lazar

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Francesco Masulli and Larry Reeker - Bioinformatics.

Bagged Ensembles of SVM for Gene Expression Data Analysis,
G. Valentini

Fuzzy Approach to DNA Microchip Analysis for HLA Typing,
F.  Masulli, S. Rovetta, R. Sensi

Gene Selection and Classification by Entropy-based Recursive
Feature Elimination,
C. Furlanello, S. Merler, M.Serafini, G. Jurman,

Artificial Neural Networks Methods for Identification of the
Most Relevant Genes  from Gene Expression Array Data,
Z. Boger

Bioinformatics, Ontologies and Machine-Learning,
L. Reeker,  A.T. Jones

Maximum Likelihood techniques for the temporal analysis of transcriptional
regulation in the mammalian ear.
M. Milo, M.N. Rivolta, M.C. Holley


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Eduardo Bayro-Corrochano - Geometric Neurocomputing.

1) Geometry of information surfaces and a computational model for the
   Anterior Singular Cortex in Perception of Pain.
   Hamid Eghbalnia, Miroslav Backonja, Dian Fallahati, Liya Wang, and
Michael
   Behrman, A. Assari.
   assadi@math.wisc.edu
2) Perceptual separability of psychologic
al dimensions in a geometric
context.
   Jim Townsend, Indiana University, Bloomington, IN; jtownsen@indiana.edu
   Jesse Spencer-Smith, Beckman Institute, University of Illinois,
Urbana, IL

   jbspence@uiuc.edu
3) Spherical Decision Surfaces Using Conformal Modelling
   V. Banarer, C. Perwass, G. Sommer, Cognitive Systems Group, Christian
Albrechts University,
   Kiel, Germany.
4) Design of kernels for SupportMultiVectorMachines involving
   the Clifford product
   Bayro-Corrochano E., Vallejo R. and Arana N.
   CINVESTAV, Unidad Guadalajara, Mexico
   Computer Science Department, GEOVIS Laboratory
   edb@gdl.cinvestav.mx
 5)  A lattice algebra approach to neural computation.
      Gerhard X. Ritter
      Department of Computer & Information Science & Engineering,
      Univeristy of Florida
      ritter@cise.ufl.edu
6) The role of quaternion Fourier descriptors for the preprocessing in
neural computing.
   Bayro-Corrochano E., Castillo N. and Naranjo M.
   CINVESTAV, Unidad Guadalajara, Mexico
   Computer Science Department, GEOVIS Laboratory
   edb@gdl.cinvestav.mx
   LASMEA-GRAVIR Blais Pascal University, Clermont-Ferrand, France
   naranjo@custsv.univ-bpclermont.fr

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Robert J. Marks and John Vian - Applications in Aerospace.

Propulsion System Vibration Diagnostics
Xiao Hu and Donald C. Wunsch II (University of Missouri - Rolla)

Restoration of missing sensors on a jet aircraft engine using trained
autoencoders
Sre Narayanan, B.B. Thompson, R.J. Marks II (University of Washington)
John Vian and Debra Coleman (Boeing Phantom Works)

Identification of False Positive Airplane Maintenance Messages
Oscar Kipersztok and Dragos Margineantu (Boeing Phantom Works)

Union Rule Configuration of Fuzzy Feedforward Neural Networks
Jeffrey J. Weinschenk and R.J. Marks II (University of Washington)
William E. Combs (The Boeing Company)

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Robert Kozma, Ali Minai and DeLiang Wang - Dynamical Aspects of 
Information Encoding in Neural Networks.

Dynamical Aspects of Information Encoding I: Theoretical Issues

Neurobiological theory of meaning in perception
Walter Freeman (UC Berkeley)

The role of temporal coding in the processing of relational information
in the mind-brain
Lokendra Shastri (UC Berkeley)

Can we understand neural computation in terms of pattern languages?
Peter Andras (Univ. of Newcastle, UK)
On a pulse-coupled network of spiking neurons having quantized state
Hiroyuki Torikai (Hosei Univ., Japan)

Dynamical Aspects of Information Encoding II: Cognitive Neuroscience

Dynamics arising from learning in a hippocampal model
Chip Levy (Univ. of Virginia)

Theta rhythm and the encoding and retrieval of episodic memory and task
rules in hippocampus and prefrontal cortex
Mike Hasselmo (Boston Univ.)

Chaotic model of learning spatial navigation
Robert Kozma (Univ. of Memphis)

Processing of analogy in the thalamocortical circuit
Yoonsuck Choe (Texas A&M)

Dynamical Aspects of Information Encoding III: Perceptual Processing

Dynamic cortical cooperations related to visual perception
Reinhard Eckhorn (Philipps Univ. of Marburg, Germany)

A dynamical model for multi-scale pixel clustering
Liang Zhao (Univ. of Sao Paulo, Brazil)

Monaural speech segregation and oscillatory correlation
DeLiang Wang (Ohio State Univ.)

Recurrent timing nets for auditory scene analysis
Peter Cariani (Harvard Univ.)

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John Weng and Olaf Sporns - Autonomous Mental Development

Lessons from ethology for computational models of development
Bruce Blumberg, Matt Berlin, Daphna Buchsbaum, Marc Downie, Derek Lyons, Jennie Cochran.  
Media Lab. MIT.

Automatic language acquisition by an autonomous robot 
Stephen Levinson, Weiyu Zhu, Danfeng Li, Kevin Squire, Ruei-sung Lin, Matthew Kleffner, Matthew McClain, and Johnny Lee.  
University of Illinois at Urbana-Champaign.

Early integration of vision and manipulation
Giorgio Metta, Paul Fitzpatrick.  
AI Lab. MIT.

Learning communities: Connectivity and dynamics of interacting agents
Tanzeem Choudhury, Brian Clarkson, Sumit Basu and Alex Pentland. 
Media Lab. MIT.

Investigating models of social development with a humanoid robot
Brian Scassellati. 
Yale University.

Neuromodulation in a learning robot: Interactions between neural plasticity and behavior.
Olaf Sporns, William H. Alexander.  
Indiana University.
                                                     
Generating structure in sensory data through coordinated motor activity
Olaf Sporns, Teresa Pegors.  
Indiana University.

Investigating the emergence of shared attention: A progress report
Jochen Triesch, Eric Carlson, Gedeon Deak, and Javier Movellan. 
University of California at San Diego.

Developing early senses about the world: "Object permanence" and visuoauditory real-time learning
Juyang Weng, Yilu Zhang, and Yi Chen
Michigan State University                                          

Note:  this session consists of 8 time slots of presentation.   The two presentations by Indiana University use a single time slot. 
      
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