| Instructor | Michael Gastpar | Instructor | Emre Telatar | Instructor | Ruediger Urbanke | |
| Office | INR 130 | Office | INR 117 | Office | INR 116 | |
| [email protected] | [email protected] | [email protected] | ||||
| Office Hours | By appointment | Office Hours | By appointment | Office Hours | By appointment | |
| Teaching Assistant | Su Li | [email protected] | Office | INR034 | ||
| Admin Assistant | Muriel Bardet | [email protected] | Office | INR137 |
| Lectures | Monday | 09:15 – 11:00 Room: INM200 |
| Friday | 08:15 – 10:00 Room: INM201 | |
| Exercises | Friday | 10:15 – 12:00 Room: INM201 |
| Language: | English | |
| Credits : | 6 ECTS |
Official Prerequisites: COM-300 Modèles stochastiques pour les communications (or equivalent)
Here is a link to official coursebook information).
Homework:
Some Homework will be graded…
Grading:
If you do not hand in your final exam your overall grade will be NA. Otherwise, your grade will be determined based on the following weighted average:
10 % for the Homework, 90 % for the Final Exam.
Special Announcements
Last year’s Final Exam and Solutions.
Detailed Schedule
(tentative, subject to changes)
| Date | Topics Covered | Lectures | Exercises | |
|---|---|---|---|---|
| Review | HW0 Sol0 | |||
| 21/9 | General Introduction ; Review Linear Algebra, Probability Exercise: Review Session (Linear Algebra, Probability) (MG) |
Chapter 2 | Handout | |
| Information Measures | ||||
| 24/9 | Basic Information Measures (ET) | Handout | ||
| 28/9 | (ET) | HW1 | ||
| 01/10 | (ET) | |||
| 05/10 | (ET) | Sol1 | ||
| Estimation and Detection | ||||
| 08/10 | Optimum Detection and Estimation ; MMSE (MG) | |||
| 12/10 | Parameter estimation ; Fisher information ; Cram`er-Rao bound (MG) | HW2 | ||
| 15/10 | Exploration bias and generalization guarantees (II) | Handout1 | ||
| 19/10 | via information measures (II) | Handout2 | Sol2 | |
| Exponential Families | ||||
| 22/10 | Exponential families ; Max Entropy problems (RU) | Chapter 4 | ||
| 26/10 | Boltzmann distribution ; Exponential families (RU) | HW3 Sol3 | ||
| Compression and Quantization | ||||
| 29/10 | Compression and Quantization (ET) | |||
| 02/11 | Compression and Quantization (ET) | HW4 | ||
| 05/11 | Compression and Quantization (ET) | |||
| 09/11 | Compression and Quantization (ET) | Sol4 | ||
| Multi-Arm Bandits | ||||
| 12/11 | Multi-armed Bandits : Explore & Exploit (RU) | Chapter 7 | ||
| 16/11 | Multi-armed Bandits : UCB algorithm (RU) | HW5 | ||
| 19/11 | Multi-armed Bandits : Converse bound (RU) | Sol5 | ||
| 23/11 | Multi-armed Bandits : Variations (RU) | |||
| Signal Representations | ||||
| 26/11 |
Signal Representation : Fourier, Sparse Fourier, (MG)
|
Chapter 6 | ||
| 30/11 | Wavelets, Compressed sensing? (MG) | HW6 | ||
| 03/12 | Wiener Filter (MG) | |||
| 07/12 | LMS Adaptive Filter (MG) | Sol6 | ||
| Distribution Estimation | ||||
| 10/12 | Distribution Estimation ; Property Testing and Estimation (RU) | Chapter 8 | ||
| 14/12 | Distribution Estimation ; Property Testing and Estimation (RU) | HW7 | ||
| 17/12 | Distribution Estimation ; Property Testing and Estimation (RU) | |||
| 21/12 | Distribution Estimation ; Property Testing and Estimation (RU) | Sol7 |