Dear ,

We really thanks you all for accepting to be a 
Program Committee member of the 4th ICNNAI conference.

Sorry for your spending time, but in order for review 
process efficient and effective, please choose 
at least 5 topics from the list bellow
or specify them in your own words, if any. And then
let us know it.

For example:
-----------------------------------------------
(A-03), (A-04), (B-01), (C-02), (E-05), (F-03), 
and (Data-mining using a Fuzzy NN)
-----------------------------------------------

This is for us to be able to specify specialties of 
each of the reviewers. 

Thank you in advance for your cooporation.

Also please find attached 1st CFP and we would appreciate
it if you give us any comment on the initial vergion of 
the CFP.

Looking forward to seeing you in Brest.

With best wishes,

Conference Chair:  Prof. Vladimir Golovko:
Co-chair:  Prof. Akira Imada
_________________________________________
Intelligent Information Technologies Dept.
Brest State Technical University
Moskowskaja 267, Brest, Belarus
phone: +375-162-42-6321
fax:   +375-162-42-2127

   

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(The list is according to the NIPS-2005 categorization 
of topics.)
----------------------------------------------------------
[A} Algorithms and NN Architectures: 
(A-01) statistical learning algorithms, 
(A-02) kernel methods, 
(A-03) graphical models, 
(A-04) Gaussian processes, 
(A-05) dimensionality reduction
(a-06) manifold learning, 
(A-07) model selection, 

[B] Applications: 
(B-01) time series prediction, 
(B-02) bioinformatics, 
(B-03) text or web analysis, 
(B-04) multimedia processing,
(B-05) robotics

[C] Brain Imaging: 
(C-01) neuroimaging, 
(C-02) cognitive neuroscience, 
(C-03) EEG (electroencephalogram), 
(C-04) ERP (event related potentials), 
(C-05) MEG (magnetoencephalogram), 
(C-06) fMRI (functional magnetic resonance imaging), 
(C-07) brain mapping, 
(C-08) brain segmentation, 
(C-09) brain computer interfaces. 

[D] Cognitive Science and Artificial Intelligence: 
(D-01) theoretical/computational/experimental studies of perception, 
(D-02) psychophysics, 
(D-03) human or animal learning, 
(D-04) memory, 
(D-05) reasoning, 
(D-06) problem solving,  
(D-07) natural language processing,
(D-08) neuropsychology. 

[E] Control and Reinforcement Learning: 
(E-01) decision and control, 
(E-02) exploration, 
(E-03) planning, 
(E-04) navigation, 
(E-05) Markov decision processes, 
(E-06) game-playing, 
(E-07) multi-agent coordination, 
(E-08) computational models of classical operant conditioning. 

[F] Emerging Technologies: 
(F-01) analog and digital VLSI, 
(F-02) neuromorphic engineering, 
(F-03) computational sensors and actuators, 
(F-04) microrobotics, 
(F-05) bioMEMS, 
(F-06) neural prostheses, 
(F-07) photonics, 
(F-08) molecular quantum computing. 

[G] Learning Theory: 
(G-01) generalization, 
(G-02) regularization
(G-03) model selection, 
(G-04) Bayesian learning, 
(G-05) statistical physics of learning, 
(G-06) online learning and competitive analysis, 
(G-07) hardness of learning and approximations, 
(G-08) large deviations and asymptotic analysis, 
(G-09) information theory. 

[H] Neuroscience: (theoretical/experimental studies of 
    processing and transmission of information 
    in biological neurons and networks)
(H-01) spike train generation, 
(H-02) synaptic modulation, 
(H-03) plasticity and adaptation. 

[I] Speech and Signal Processing: 
(I-01) recognition, 
(I-02) coding, 
(I-03) synthesis, 
(I-04) denoising, 
(I-05) segmentation, 
(I-06) source separation, 
(I-07) auditory perception, 
(I-08) psychoacoustics, 
(I-08) dynamical systems, 
(I-10) recurrent networks, 
(I-11) Language Models, 
(I-12) Dynamic and Temporal models. 

[J] Visual Processing: 
(J-01) biological and machine vision, 
(J-02) image processing and coding, 
(J-03) segmentation, 
(J-04) object detection and recognition, 
(J-05) motion detection and tracking, 
(J-06) visual psychophysics, 
(J-07) visual scene analysis and interpretation. 

[K]
(K-01) combinatorial optimization. 
(K-02) artificial life