## EE 378A: Statistical Signal Processing## AnnouncementsHomework 3 solution is out!
Homework 3 is out! It's due on Wednesday, 6/1.
Homework 2 solution is out!
Homework 2 is out! It's due on Monday, 5/9.
Final project is out! Please complete the preference survey by midnight this Friday, 4/22.
Homework 1 solution is out!
Homework 1 is out! It's due on Friday, 4/15.
Welcome to the EE378a course!
We will use Coursework for grade records. Please go to Coursework to look up your homework grades.
## Course OverviewThis year's EE378A offering has been substantially revised to include recent research results in data science, as well as a comparison between and analysis of existing frameworks for data analysis and processing. Among other questions, we will consider the following: What is the difference between statistical decision theory and learning theory? What is the difference between statistics and machine learning? What are the bias-variance trade-offs in decision theory and in learning theory? How can we incorporate prior knowledge in real world problems, and derive effective algorithms? Can we make inference on data without prior assumptions on the data generation mechanisms?
We will also analyze algorithms that perform well in one theoretical framework but are highly sub-optimal in another, and contrast with algorithms that perform well simultaneously under multiple frameworks. Students will be exposed to a variety of disciplines, and connections between them. ## LogisticsThe course will cover and emphasize the importance of both theory and algorithms. Grading will be based primarily on about 4 homework sets, and a final project. Project topics will be offered, but students are welcome to propose their own project topics. |