From Computational Learning and Motor Control Lab

Teaching: CS 542 Neural Computation with Artificial Neural Networks


Time and Place:

2:00-3:20 Mondays & Wednesdays, SLH 100


Course Description:

The course will introduce fundamental and advanced techniques of neural computation with statistical neural networks. Skills from this course will be beneficial for applied and basic research in artificial intelligence (e.g., robotics, machine learning, process control), computational neuroscience (e.g., motor control, functional brain modeling) and cognitive sciences (e.g., perception, memory, reasoning). Topics of the course will initially briefly survey classical supervised and unsupervised learning methods, such as backpropagation, radial basis functions, clustering, Kohonen networks, Boltzman machines, and principal components. Afterwards, in accordance with the interests of the participants, modern concepts in learning will be introduced, possibly including nonparametric learning, reinforcement learning, mixtures models, belief networks, minimum description length, maximum likelihood, entropy methods, independent component analysis, support vector machines, gaussian processes, etc.

Class Format:

The course consists of lectures with discussions, reading assignments, and homework assignments using dedicated neural network software in Matlab. Each student will carry out an independent final project in an area subject to the instructor's approval. At the end of the course there will be a short written exam reviewing the basics of the course.



Basic knowledge in linear algebra, calculus, and programming in C (or another language), or permission by instructor.



Dr. Stefan Schaal
Associate Professor
University of Southern California
Ronald Tutor Hall RTH-417
Los Angeles, CA 90089-2520
phone: (213) 740 9418
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Mrinal Kalakrishnan
University of Southern California
Ronald Tutor Hall RTH-417
Los Angeles, CA 90089-2520
phone: (213) 740 6717
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Office Hours:

According to email arrangement with instructor cgi-bin/mimetex.cgi -d '\textrm{}' >pub/cache/5d427ff336f2e07d5db3ef717f14568a.gif or TA cgi-bin/mimetex.cgi -d '\textrm{}' >pub/cache/bae393fb5e9bc37011e584b2aaa9ec66.gif.

Academic Integrity:

All students are required to abide by the USC code of Academic Integrity. Violation of that Code will be dealt with as described in SCAMPUS. If you have any questions about the responsibilities of either students, faculty, or graders under this policy, contact the instructor or the Office of Student Conduct.

Disabilities and Academic Accomodations:

Students requesting academic accomodations based on a disability are required to register with Disability Services and Programs (DSP) each semester. A letter of verification for approved accomodations can be obtained from DSP when adequate documentaion is filed. Please be sure the letter is delivered to the instructor (or TA) as early in the semester as possible. DSP is open Monday-Friday, 8:30-5:00. The office is in Student Union 301 and their phone number is (213) 740-0776.

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