Machine Learning Seminar

CS 570
Computer Science Department, Portland State University

Winter 2019


Time: Thursdays, 4:00-5:30pm

Location: FAB 88-03

Instructor: Melanie Mitchell, FAB 115-13, (503) 725-2412, e-mail
Office hours: Tuesdays and Thursdays,10am-11am, or by appointment

Course Mailing list: mlseminar2019@cs.pdx.edu

Course description: This course is a one-credit graduate seminar for students who have already taken a course in Machine Learning. Students will read and discuss recent papers in the Machine Learning literature. Each student will be responsible for presenting at least one paper during the term. This one-credit course will be offered each term, and students may take it multiple times. CS MS students who take this course for three terms may count it as one of the courses for the "Artificial Intelligence and Machine Learning" masters track requirement.

Prerequisites: CS 445/545 or permission of the instructor.

Textbook: None. We will read recent papers from the literature.

Course Work and Homework: One or more papers will be assigned per week for everyone in the class to read, along with a list of questions about the paper(s) that each student needs to answer before the following class. Each week one or more students will be assigned as discussion leaders for the week's papers.

Topic for Winter Term 2019: Transfer Learning

Schedule for Fall Term 2018: This will be progressively filled in during the term.

Date

Presenter(s)

Readings

Questions

January 10

Melanie

Kansky et al., Schema networks: Zero-shot transfer with a generative causal model of intuitive physics

Week 1 Slides

January 17

Asher and Andreas

Rusu et al., Progressive neural networks

Gamrian and Goldberg, Transfer learning for related reinforcement learning tasks via image-to-image translation

Week 2 Questions

January 24

Kevin and Chris

Li et al., Learning without forgetting

Rosenfeld and Tsotsos, Incremental learning through deep adaptation

January 31

Sean and Alex

Ge and Yu, Borrowing treasures from the wealthy: Deep transfer learning through selective joint fine-tuning

Ngiam et al., Domain adaptive transfer learning with specialist models

February 7

February 14

February 21

February 28

March 7

March 14