|In this semester, we will cover two different topics: IoT and deep learning. The first part of this lecture will focus on wireless adhoc network technology that provide low energy and low latency lightweight communication for WSN (wireless sensor networks) and MANET (mobile adhoc networks). The second part of this class will focus on deep learning techniques of artificial intelligence. Recently, deep learning techniques are used not only for machine learning but also applied to other fields of information technology as well as to the other fields of engineering and science in general. We will discuss the basic concepts of deep learning such as CNN and RNN by studying the classical papers of machine learning and deep learning. Then, we move to more recent topics of deep learning such as reinforcement learning (RL) and generative adversarial networks (GAN) by reviewing the recent research papers in deep learning.|
1. Lecture Note 1 was updated on September 3rd.
2. Lecture Note 2 was updated on September 10th.
3. Lecture Note 3 was updated on September 18th.
4. Lecture Note 4 was updated on October 1st.
5. Lecture Note 5 was updated on October 16th.
6. Lecture Note 6 was updated on October 16th.
7. Lecture Note 7 was updated on October 30th.
8. Lecture Note 8 was updated on November 6th.
▣ Lecture slide
▣ Paper Presentation
Paper List : Paper List.docx
Convolutional Neural Network (12 papers)
Natural Language Processing / Recurrent Neural Network (12 papers)
Optimization / Training Techniques (10 papers)
Understanding / Generalization / Transfer (7 papers)
▣ Reading List