Difference between revisions of "Exploring NAS spaces with C-BRED"

Revision as of 14:12, 24 February 2022

Introduction

Project description

Project Description

Skills and project character

Skills

Required:

• Fundamental concepts of deep learning (convolutional neural networks, backpropagation, computational graphs)
• Python programming
• Familiarity with the PyTorch deep learning framework
• Familiarity with the scikit-learn Python package

Optional:

• Familiarity with the ONNX standard
• Familiarity with dimensionality reduction, clustering, and kernel methods
• Familiarity with elementary concepts of statistics (random variable, probability distribution)

Project character

• 10% Software engineering
• 60% Python coding
• 30% Data science applied to deep learning

Logistics

The student and the advisors will meet on a weekly basis to check the progress of the project, clarify doubts, and decide the next steps. The student and the advisors will also have regular code reviews, whose frequency will depend on the stage of the project. The schedule of these meetings will be agreed at the beginning of the project by both parties. Of course, additional meetings can be organised to address urgent issues.

At the end of the project, you will have to present your work during a 15 minutes (20 minutes if carried out as a Master Thesis) talk in front of the IIS team and defend it during the following 5 minutes discussion.

Professor

Luca Benini

Status: Available

We are looking for 1 Master student. It is possible to complete the project either as a Semester Project or a Master Thesis.

Supervisors: Matteo Spallanzani spmatteo@iis.ee.ethz.ch, Thorir Mar Ingolfsson