chucko@saturn.ucsc.edu (Chuck Stein) (06/11/88)
The University of California
Eighteenth Annual
INSTITUTE IN COMPUTER SCIENCE
presents courses in:
* Scientific Visualization * Fault Tolerant Computing
* Parallel Computation * Image Engineering
* Data Compression * Machine Learning
at
Techmart, Santa Clara
and
on campus in Santa Cruz
Following is a course description for:
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Artificial Neural Networks
August 1-3
Instructor: BART KOSKO
X415 Computer & Information Sciences (2)
This course offers a rigorous introduction to the mechanics of
artificial neural networks. It is aimed at an interdisciplinary audience
with emphasis on engineering and artificial intelligence. Designed as
an active process, the course will oblige participants to undertake
assignments including written work. Upon completion, attendees will
have a working knowledge of several state-of-the-art neural network
technologies.
Overview :
Artificial neural networks are programmable dynamical systems. Their
global properties can often be designed to carry out practical
information processing--pattern storage, robust recall, fuzzy
association, distributed prediction, inductive inference, and
combinatorial optimization. Artificial neural networks are especially
well suited for realtime pattern recognition and nearest neighbor
matching in large databases. Some continuous and diffusion networks
can perform global optimization. Some networks can learn complex
functional mappings simply by presenting them with input-output
pairs. Some fuzzy knowledge networks can represent, propagate, and
infer uncertain knowledge in contexts where traditional AI decision-
tree graph search cannot be applied.
Prerequisite: Background in calculus, matrix algebra, and some
probability theory.
Schedule
Monday:
*Associative Memory
symbolic vs. subsymbolic processing
preattentive and attentive processing
global stability
bidirectional associative memories (BAM)
optical BAMs
error-correcting decoding
temporal associative memory, avalanches
optimal linear associative memory
Tuesday:
*Global Stability and Unsupervised Learning
continuous BAMs and the Cohen-Grossberg Theorem
neurocircuits for combinatorial optimization
Hebb, differential Hebb, and competitive learning
adaptive BAMs
Grossberg Theory
adaptive resonance theory
adaptive vector quantization
counter-propagation
Wednesday:
*Supervised Learning and Fuzzy Knowledge Processing
lean-mean-square algorithm
backpropagation
simulated annealing
Geman-Hwang theorem for Brownian diffusions
Cauchy vs. Boltzmann machines
fuzzy entropy and conditioning
fuzzy associative memories (FAMs)
fuzzy cognitive maps (FCMs) and learning FCMs
Instructor: BART KOSKO, Assistant Professor of Electrical
Engineering at the University of Southern California
Fee: Credit, $895 (EDP J2478)
Dates: Three days, Mon.-Wed., Aug. 1-3, 9 a.m.-5 p.m.
Place: Techmart, 5201 Great America Pkwy., Santa Clara
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RESERVATIONS:
Enrollment in these courses is limited. If you wish to attend a course
and have not pre-registered, please call (408) 429-4535 to insure that
space is still available and to reserve a place.
DISCOUNTS:
Corporate, faculty, IEEE member, and graduate student discounts and
fellowships are available. Please call Karin Poklen at (408) 429-4535
for more information.
COORDINATOR:
Ronald L. Smith, Institute in Computer Science, (408) 429-2386.
FOR FURTHER INFORMATION:
Please write Institute in Computer Science, University of California
Extension, Santa Cruz, CA 95064, or phone Karin Poklen at (408) 429-
4535. You may also enroll by phone by calling (408) 429-4535. A
packet of information on transportation and accommodations will be sent
to you upon receipt of your enrollment.