Topics in Optimization for Machine Learning Sebastian Stich


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Seminar: Topics in Optimization for Machine Learning

Optimization lies at the heart of many machine learning algorithms. This seminar teaches an overview of modern mathematical optimization methods, for applications in machine learning and data science. In particular, we will discuss the theoretical basics of stochastic optimization, scalability of algorithms to large datasets, and challenges in distributed optimization, such as for instance in decentralized or federated machine learning. We will cover a set of foundational papers, but also a selection of recent publications.


In this seminar, students will learn to present, discuss, and summarize papers in different areas of optimization for machine learning. Specifically, each student will get a single topic assigned to them, consisting of two papers (a lead and follow-up paper). Each student will

  • write a short seminar paper on the topic assigned to them, for which the two papers on the topic serve as the starting point;
  • prepare a presentation on the topic assigned to them;
  • write three short reviews on papers from a different topic, and prepare questions to ask the to the presenter of this paper/topic. The reviews will be shared among the group (in particular with the presenter of the topic).

Important Dates

  • Kick-off meeting October 25, 2021 (to be held online, via zoom).
  • The reviews (and questions) must be submitted during the semester, one review per month. You will get a short feedback after each submission. 
  • Mandatory feedback round/practice talk at least two weeks before the presentation (arrange exact time with supervisor).
  • The presentations will be organized in a block format during the semester break, in the week of February 28-March 4, 2022 (or February 14-18, 2022, dates to be fixed at the kick-off meeting). Participation is mandatory.
  • Hand-in of report: February 25, 2022, 23.59h.


  • 3 short reviews: (each contributes 10% of your final grade): Write a short review (max 1 page) on one of the papers (not the one that you are presenting) that addresses the following questions:
    1. What is the problem addressed by the paper?
    2. What was done before, and how does the paper improve on previous work?
    3. What are the strengths and the limitations of the techniques in the paper
    4. What part of the paper was difficult to understand?
    5. What are possible improvements or extensions of the techniques in the paper?

    In addition to your review you will have to submit 3 questions that you will ask the presenter of the paper.

  • Presentation: (40%). You will prepare and deliver a 30 min presentation (followed by 15 mins question/discussion) of the paper assigned to you. You will have the possibility to get feedback on your slides before the presentation.

  • Seminar Paper: (30%) You will write a seminar paper on the topic that you have presented. It must not be longer than 6 pages, not counting references and appendices. Note that appendices are not meant to provide information that is absolutely necessary to understand the paper, but rather to provide auxiliary material. Papers can be shorter, but in general the provided page limit is a good indicator of how long a paper should be.

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