Machine Learning Seminars by SimulaMet

Next Seminar

Speaker: Alexander Bronstein

Professor at Tel Aviv University, Israel

Personal Website

Time and Date: 12:00pm on Monday 18 February 2019

Location: Pilestredet 52, F318

Title: Tradeoffs between Speed and Accuracy in Inverse Problems


Solving a linear system of the type Ax + n = y with many more unknowns than equations is a fundamental ingredient in a plethora of applications. The classical approach to this inverse problem is by formulating an optimization problem consisting a data fidelity term and a signal prior, and minimizing it using an iterative algorithm. Imagine we have a wonderful iterative algorithm but real-time limitations allows only to execute five iterations thereof. Will it achieve the best accuracy within this budget? Imagine another setting in which an iterative algorithm pursues a certain data model, which is known to be accurate only to a certain amount. Can this knowledge be used to design faster iterations? In this talk, I will try to answer these questions by showing how the introduction of smartly controlled inaccuracy can significantly increase the convergence speed of iterative algorithms used to solve various inverse problems. I will also elucidate connections to deep learning an provide a theoretical justification of the very successful LISTA networks. Examples of applications in computational imaging and audio processing will be provided.

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Past Seminars:

Autumn 2018

Spring 2019