| Weekly Schedule and Class Notes |
- Lecture notes : all notes will be posted in this section.
- It is your responsibility to download, print and bring the notes to the class. Notes will be available 24 hours before each class.
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Week |
Date |
Topic |
Reading |
Assignments |
Notices and Dues |
Notes |
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1 |
03/08 |
1. Introduction and Course Organization |
Lecture Note |
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2 |
03/15 |
2. Data Entropy and Cross Entropy 3. Data Mastking and Convolution 4. Relationship between Deep Learning and Nonlinear Programming 5. Hybrid Deep Learning |
Lecture Note |
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3 |
03/22 |
6. Deep learning-based Data generation 7. Generative Adversarial Network |
Lecture Note |
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Image to Image generation / data to data generation |
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4 |
03/29 |
8. Principle of Optimization (differential, Gradient, non-differential, pertubation) 9. Metaheurstics I (Simulated Annealing) |
Lecture Note |
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5 |
04/05 |
10. Metaheuristrics II (Harmony Search) |
Lecture Note |
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6 |
04/12 |
11. FONC / SONC 12. Dual and KKT condition in NLP (Lagrange Mulipliers) 13. Strong duality / weak duality 14. NLP in Deep Learning |
Lecture Note |
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7 |
04/19 |
15. Genetic Algorithm |
Lecture Note |
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8 |
04/26 |
Midterm(I) |
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9 |
05/03 |
Midterm (II) |
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10 |
05/10 |
16. Deep Neural network and Backpropagation |
Lecture Note |
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11 |
05/17 |
17. Deep Learning Implementation (I) |
Lecture Note |
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12 |
05/24 |
18. Research reading |
Lecture Note |
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13 |
05/31 |
19. Matlab Interface - Inside function, Guide, Appdesigner |
Lecture Note |
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14 |
06/07 |
20. Deep Learning - Non overfitting methods (Dropout, batch normalization, some activation functions) |
Lecture Note |
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15 |
06/14 |
Reading day |
Lecture Note |
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16 |
06/21 |
Final Exam |
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