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General Information | Resources | Weekly Schedule | Lecture Notes | Example Code | Read-Only Board |
I. General Information |
Instructor:Dr. Yoonsuck Choe |
Grader:Anurag Garg |
Math 304 (linear algebra) and 308 (differential equations) or approval of instructor. (Actually, if you are mildly familiar with linear algebra and have taken calculus, you should be fine.)Prior programming experience is not a prerequisite, but there will be programming assignments. It if preferred that you already took 633 machine learning.
MWF 11:30am-12:20pm. ETB 1020.
Basic concepts in neural computing; functional equivalence and convergence properties of neural network models; associative memory models; associative, competitive and adaptive resonance models of adaptation and learning; selective applications of neural networks to vision, speech, motor control and planning; neural network modeling environments.
The official textbook for this class will be:However, a lot of overlapping material appear in the older edition:
- Simon Haykin, Neural Networks and Learning Machines, 3rd edition, Prentice Hall, Upper Saddle River, NJ, 2008. ISBN 0131471392.
so this could be a good, cheaper alternative.
- Simon Haykin, Neural Networks: A Comprehensive Foundation, Second edition, Prentice-Hall, Upper Saddle River, NJ, 1999. ISBN 0-13-273350-1.
Other books: see slide01.pdf.
See the Weekly Schedule section for more details.
Grading will be on the absolute scale. The cutoff for an `A' will be 90% of total score, 80% for a `B', 70% for a `C', 60% for a `D', and below 60% for an 'F'.Attendance will be checked on a random basis. More than 3 absences will result in a deduction of 5 points (out of 100) from the final weighted total.
AGGIE HONOR CODE: An Aggie does not lie, cheat, or steal or tolerate those who do.Upon accepting admission to Texas A&M University, a student immediately assumes a commitment to uphold the Honor Code, to accept responsibility for learning, and to follow the philosophy and rules of the Honor System. Students will be required to state their commitment on examinations, research papers, and other academic work. Ignorance of the rules does not exclude any member of the TAMU community from the requirements or the processes of the Honor System.
For additional information please visit: http://www.tamu.edu/aggiehonor/
Local Course Policy:
- All work should be done individually and on your own unless otherwise allowed by the instructor.
- Discussion is only allowed immediately before, during, or immediately after the class, or during the instructor's office hours.
- If you find solutions to homeworks or programming assignments on the web (or in a book, etc.), you may (or may not) use it. Please check with the instructor.
The Americans with Disabilities Act (ADA) is a federal anti-discrimination statute that provides comprehensive civil rights protection for persons with disabilities. Among other things, this legislation requires that all students with disabilities be guaranteed a learning environment that provides for reasonable accommodation of their disabilities. If you believe you have a disability requiring an accommodation, please contact Disability Services, currently located in the Disability Services building at the Student Services at White Creek complex on west campus or call 979-845-1637. For additional information, visit http://disability.tamu.edu.
II. Resources |
III. Weekly Schedule and Class Notes |
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1 | 1/18 | Martin Luther King day: No class | Notice: Undefined offset: 4 in /home/faculty/choe/web_project/636-16spring/index.php on line 395 | |||
1 | 1/20 | Introduction | Chap 1 (Intro chapter, 3rd ed) | slide01.pdf |
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1 | 1/22 | Introduction | Chap 1 (Intro chapter, 3rd ed) | slide01.pdf |
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2 | 1/25 | Introduction | Chap 1 (Intro chapter, 3rd ed) | slide01.pdf |
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2 | 1/27 | Learning process | Chap 2 (Intro chapter sections 8, 9) | slide02.pdf |
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2 | 1/29 | Learning process | Chap 2 (Intro chapter sections 8, 9) | slide02.pdf |
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3 | 2/1 | Learning process | Chap 2 (Intro chapter sections 8, 9) | Homework 1 assigned | slide02.pdf |
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3 | 2/3 | Single-layer perceptrons | Chap 3 (Chap 1, Chap 3) | slide03.pdf |
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3 | 2/5 | Single-layer perceptrons | Chap 3 (Chap 1, Chap 3) | slide03.pdf |
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4 | 2/8 | Single-layer perceptrons | Chap 3 (Chap 1, Chap 3) | slide03.pdf |
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4 | 2/10 | Single-layer perceptrons | Chap 3 (Chap 1, Chap 3) | slide03.pdf |
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4 | 2/12 | Multi-layer perceptrions | Chap 4 | Homework 2 assigned | Homework 1 due | slide04.pdf |
5 | 2/15 | Multi-layer perceptrions | Chap 4 | slide04.pdf |
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5 | 2/17 | Multi-layer perceptrions | Chap 4 | slide04.pdf |
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5 | 2/19 | Multi-layer perceptrions | Chap 4 | slide04.pdf |
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6 | 2/22 | Multi-layer perceptrions | Chap 4 | slide04-suppl.pdf |
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6 | 2/24 | Radial-basis functions | Chap 5 | slide05.pdf |
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6 | 2/26 | Radial-basis functions | Chap 5 | Homework 3 assigned | slide05.pdf |
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7 | 2/29 | Radial-basis functions | Chap 5 | Homework 2 due | slide05.pdf |
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7 | 3/2 | Special topic | Biologically inspired models | slide06.pdf |
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7 | 3/4 | Special topic | Biologically inspired models | slide06.pdf |
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8 | 3/7 | Exam 1 (in class) | Notice: Undefined offset: 4 in /home/faculty/choe/web_project/636-16spring/index.php on line 395 | |||
8 | 3/9 | Deep learning | slide-dl.pdf |
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8 | 3/11 | Deep learning | Homework 3 due | slide-dl.pdf |
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9 | 3/14 | Spring Break | No class | Notice: Undefined offset: 3 in /home/faculty/choe/web_project/636-16spring/index.php on line 384 Notice: Undefined offset: 3 in /home/faculty/choe/web_project/636-16spring/index.php on line 385 | Notice: Undefined offset: 4 in /home/faculty/choe/web_project/636-16spring/index.php on line 395||
9 | 3/16 | Spring Break | No class | Notice: Undefined offset: 3 in /home/faculty/choe/web_project/636-16spring/index.php on line 384 Notice: Undefined offset: 3 in /home/faculty/choe/web_project/636-16spring/index.php on line 385 | Notice: Undefined offset: 4 in /home/faculty/choe/web_project/636-16spring/index.php on line 395||
9 | 3/18 | Spring Break | No class | Notice: Undefined offset: 3 in /home/faculty/choe/web_project/636-16spring/index.php on line 384 Notice: Undefined offset: 3 in /home/faculty/choe/web_project/636-16spring/index.php on line 385 | Notice: Undefined offset: 4 in /home/faculty/choe/web_project/636-16spring/index.php on line 395||
10 | 3/21 | Deep learning | slide-dl.pdf |
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10 | 3/23 | Self-organizing maps | Chap 9 | slide07.pdf |
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10 | 3/25 | Reading day: No class | Notice: Undefined offset: 4 in /home/faculty/choe/web_project/636-16spring/index.php on line 395 | |||
11 | 3/28 | Self-organizing maps | Chap 9 | slide07.pdf slide07-suppl.pdf |
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11 | 3/30 | Online guest lecture (class will not meet: view the youtube lecture on your own) | Visualizing and Understanding Deep Neural Networks by Matt Zeiler on YouTube | Homework 4 assigned | Notice: Undefined offset: 4 in /home/faculty/choe/web_project/636-16spring/index.php on line 395 | |
11 | 4/1 | Self-organizing maps/Neurodynamics | Chap 9, Chap 14 (3rd ed. Chap 13) | slide07.pdf slide07-suppl.pdf slide08.pdf |
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12 | 4/4 | Neurodynamics | Chap 14 (3rd ed. Chap 13) | slide08.pdf |
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12 | 4/6 | Principal components analysis | Chap 8 | slide10.pdf |
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12 | 4/8 | Guest lecture | Jaewook Yoo: (1) Development of motor map using GCAL (LISSOM variant); (2) Evolving neural network for simple tool use. | slide.pdf |
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13 | 4/11 | PCA |
Chap 8 |
slide10.pdf |
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13 | 4/13 | PCA, Information theoretic models | Chap 8, Chap 10, ICA |
slide10.pdf slide11.pdf |
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13 | 4/15 | Info theoretic models |
Chap 10, ICA; |
Homework 4 due | slide11.pdf |
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14 | 4/18 | Info theoretic models; ICA |
Chap 10, ICA; |
slide11.pdf |
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14 | 4/20 | ICA ; Support Vector Machines |
ICA; Chap 6; |
slide11.pdf slide09.pdf |
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14 | 4/22 | Support Vector Machines |
Chap 6; |
slide09.pdf |
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15 | 4/25 | Exam 2 (in class) | Notice: Undefined offset: 4 in /home/faculty/choe/web_project/636-16spring/index.php on line 395 | |||
15 | 4/27 | Special topic | Salient contour detection. Sarma and Choe (2006), Lee and Choe (2003) |
slide12.pdf |
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15 | 4/29 | Special topic | Sensorimotor learning. Choe and Smith (2006), Choe et al. (2007), etc. |
slide-sida.pdf |
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16 | 5/2 | Deep learning | Notice: Undefined offset: 4 in /home/faculty/choe/web_project/636-16spring/index.php on line 395 | |||
16 | 5/4 | Deep learning; Course wrap up. Class meets on 5/3 Tuesday (redefined Friday) | Notice: Undefined offset: 4 in /home/faculty/choe/web_project/636-16spring/index.php on line 395 |