In recent years, machine learning have been increasingly used to predict, enhance, and even replace human decision making in a wide variety of off-line and on-line applications. In this course, you will learn about recent advances in human-centered machine learning. More specifically, in the first half of the course, you will get to know about a growing set of techniques to ensure that machine learning methods fueling algorithmic decisions are fair to all and its outputs are interpretable. In the second half of the course, you will learn about machine learning methods specifically designed to understand, predict and enhance human decision making, with a particular emphasis on online social and information systems.
Instructors |
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gummadi@mpi-sws.org |
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manuelgr@mpi-sws.org |
TAs |
Office Hours |
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achakrab@mpi-sws.org |
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ade@mpi-sws.org |
Mondays 14:30 — 15:30, |
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junaid@mpi-sws.org |
Fridays 15:00 — 16:00, |
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nghlaca@mpi-sws.org |
Wednesdays 14:30 — 15:30, |
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plahoti@mpi-inf.mpg.de |
Fridays 16:00 — 17:00, |
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utkarshu@mpi-sws.org |
Wednesdays 14:30 — 15:30, |
This advanced course is open to Bachelor and Master students. Background in machine learning is required to take this course. The students must have passed one or more of the following courses:
The language of the course is English. All lectures, office hours, tutorials and communication with the course staff will be conducted exclusively in English.
There will be a midterm exam (covering material from the first half of the course), a final exam (focusing on the second half of the course), and an optional repeat exam (covering the entire course). The exams carry equal weight. All exams will be based on the material covered in lectures and readings. All exams will be open book and based on the material covered in lectures, readings, and projects.
To pass the course, a student must pass either the final or the repeat exam. Students may choose to take the repeat exam, even if they have passed the final exam, to try and improve their grade. To be admitted to the final and repeat exams, a student must (i) pass the reading and coding assignments and (ii) pass the midterm exam. To pass the reading and coding assignments, the sum of all points earned by a student in both the reading and coding assignments must be at least 50% of the maximal possible points. To pass the midterm exam, a student must score at least 30% of the maximum possible points in the exam. To pass the final exam or repeat exam, a student must score at least 30% of the maximal possible points in the exam.
Your course grade will be based on a weighted score computed from the points you earn in your successful examinations and your reading and coding assignments. If a student takes all three examinations, then the exam with the lowest result will not be considered when computing the course grade. Reading and coding assignment scores count towards 50% of the weighted score (25% for the reading assignments from the first part of the course, and 25% for the reading and coding assignments from the second part of the course) and exam scores account for the remaining 50% of the weighted score (25% each).
Before or after each lecture, you will be required to read and review a relevant paper.
Your reading assignments will consist of reading a paper and filling out a review form on the assignment submission website. The review form consists of the following questions:
To access your reading assignments, please create an account on the course's assignment submission website. After you create an account, we will give you access to the reading assignments.
Assignment deadlines: Paper reviews must be submitted by 11:59 AM (noon) on their due dates (posted on the schedule website). Assignments should be submitted using the course's assignment submission website.
Late submissions: We will apply a flexible slip date policy for late submissions. Each student is allocated an automatic extension of 4 calendar days for the entire semester. Students can use the extension on any reading assignment during the semester in hourly increments. For instance, you can hand in one reading assignment 4 days late, or one assignment 2 days late and two assignments 1 day late.
Grading: Your reading assignments will be reviewed and graded. For each assignment, you can receive 0 points (fail) or 1 point (pass). For exceptionally well written assignments, you can get 1 additional bonus point. The results will updated on Sundays and posted on this website.
After the midterm (in the second part of the course), there will be two short coding assignments.