Presentation ideas and initial resources
(Very loosely classified)
Communication problems:
1. Slepian-Wolf theorem: Distributed source coding (Primary resource: Cover&Thomas)
2. Multiple access channel: Multiple people sharing the same communication channel (Primary resource: Cover&Thomas)
3. (Degraded) broadcast channel: One transmitter broadcasting to multiple receivers (Primary resource: Cover&Thomas)
4. Wyner-Ziv: Lossy distributed source coding with side information at the receiver (Primary resource: Cover&Thomas)
5. Writing on dirty paper: Communicating over a channel when transmitter knows the state, but not the receiver (digital watermarking) (Paper)
Models:
1. Arbitrarily-varying channels: Reliable communication under channel uncertainty (Paper)
2. Online channels: Codes against online adversaries (Paper)
3. Network coding channels: Codes against network jamming (Paper)
4. Insertion-deletion channels: Channels with synchronization errors (Paper)
5. Codes for asymmetric errors: Codes for flash memories (Paper)
6. Zero-error channel codes: Channel codes for zero-error channels -- very graph-theoretic (Paper)
7. Communication complexity: Communication for computation of functions (Book)
8. Quantum channels: Communication over quantum channels (Book)
9. Wiretap channels: Information-theoretic secrecy (Paper)
Codes/Bounds:
1. Polar codes: Efficient channel decoding via successive cancellation (Paper)
2. LP decoding of Expander codes: Efficient decoding of channel codes via solving LPs (Paper)
3. List-Decoding RS codes beyond the minimum distance: "Improving" on the Singleton bound (Paper)
4. LP bound for binary codes: Upper bound for binary worst-case channel (Class notes)
5. Bound on Huffman code performance: Improved upper bound for Huffman codes (Paper)
Other problems:
1. Group testing: Identification of a small subset of defectives from a large pool via careful tests (Book)
2. Kolmogorov complexity and information theory: Computational complexity of strings, and connection with entropy (Cover&Thomas)
3. Universal portfolios: How to make money by mixing expert opinions (Cover&Thomas)
4. Gambling and information theory: How to use side-information to make money (Cover&Thomas)
5. Compressive sensing (orthogonal matching pursuit): How to reconstruct a sparse vector via just dot-products (Paper)
6. Set of entropic vectors: Characterizing the set of all possible types of random variables (Yeung)
| Name |
Topic |
|
| Yiyong Feng |
Universal portfolios |
|
| Xihao HU |
Kolmogorov complexity and information theory |
|
| Yip Kit Sang Danny |
Bound on Huffman code performance,5, 1, 4, 3, 2 | |
| Eric, Chan chun lam |
Slepian-Wolf theorem |
|
| CAI, Sheng | Gambling and information theory | |
| Zhan lei |
Writing on dirty paper |
|
| LuTan |
Group testing | |
| Chin Ho Lee | Zero-error channel codes | |
| Jiang Yunxiang | LP decoding of Expander codes | |
| Yuen Piu Hung | Wyner-Ziv | |
| Wang Qike | LP bound for binary codes | |
| Luk Hon Tung | Insertion-deletion channels | |
| Wang Limin | Compressive sensing (orthogonal matching pursuit) | |
| Wu Xixuan | Arbitrarily-varying channels | |
| Tang Wanrong |
Multiple access channel |
|
| Manson FONG | Infomax-ICA | |
Date: 12:30:00 - 14:30:00 - Tuesday, 06, December 2011
Room ERB1009