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Technical University of Munich

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Home Teaching Summer Semester 2019 Seminar: Optimization and Generalization in Deep Learning

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Seminar: Optimization and Generalization in Deep Learning

Seminar for computer science master students (IN2107).

Note to interested students: There was a lot of interest in the seminar through the matching platform. However, most of you did not send an e-mail demonstrating prerequisites. As stated in the pre-meeting and on this website, preference is given to students who showed prior exposure to the prerequisites.

Initial meeting: April 24, 4pm-6pm, room 02.09.023

Update (April 12): Due to room constraints, the time of the initial meeting had to be shifted to 4-6pm

Update (Feb 18): The block seminar week is fixed to June 3 - June 7, 6-8pm, room 02.09.023

Description

Modern deep learning methods have shown remarkable success in various domains of machine learning. However, our theoretical understanding of such methods remains rather shallow. Recently, novel ideas to better understand aspects of optimization and generalization in these models have emerged that require rethinking classical concepts in these domains. A prominent example is the implicit bias of optimization methods in an overparameterized regime. We will discuss such ideas from the computational and statistical viewpoint.

Organization

General
Pre-meeting
  • Date: Tuesday, February 5, 2019
  • Time: 4pm
  • Location: 02.09.023
Initial meeting
  • Date: Wednesday, April 24, 2019
  • Time: 12pm-2pm
  • Location: 02.09.023
Registration
  • Registration is done via the TUM matching platform
  • Attendance in the seminar sessions is mandatory
  • Preference is given to students with with a pertinent background in relevant fields of applied mathematics (Linear Algebra, Analysis, Numerical Optimization, Probability/Stats) and prior exposure to deep learning (e.g. Introduction to Deep Learning).
  • Important: When registering at the TUM matching platform, please also send an email to DL-seminar@vision.in.tum.de in which you write your full name, matriculation number and where you state and prove prior exposure to these topics, e.g., with a transcript of records, prior course projects etc..
Block Seminar Week
  • We will hold a one-week block seminar, June 3 - June 7, 6-8pm. Room: 02.09.023
  • This way the seminar does not conflict with the exam period and the evening times hopefully avoid conflicts with other lectures.
  • All talks are held in English.
Final Report

Final reports should be written in LaTeX. A template will be provided.

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Informatik IX
Chair of Computer Vision & Artificial Intelligence

Boltzmannstrasse 3
85748 Garching

info@vision.in.tum.de