Seminar  /  November 14, 2019

Deep Learning Seminar Special

This week with two talks

Speaker: Avraam Chatzimichailidis 

GradVis: Visualization and Second Order Analysis of Optimization Surfaces during the Training of Deep Neural Networks

Abstract:

Current training methods for deep neural networks boil down to very high dimensional and non-convex optimization problems which are usually solved by a wide range of stochastic gradient descent methods. While these approaches tend to work in practice, there are still many gaps in the theoretical understanding of key aspects like convergence and generalization guarantees, which are induced by the properties of the optimization surface (loss landscape).

In order to gain deeper insights, a number of recent publications proposed methods to visualize and analyze the optimization surfaces. However, the computational cost of these methods are very high, making it hardly possible to use them on larger networks.

In this talk, we present the GradVis Toolbox, an open source library for efficient and scalable visualization and analysis of deep neural network loss landscapes in Tensorflow and PyTorch. Introducing more efficient mathematical formulations and a novel parallelization scheme, GradVis allows to plot 2D and 3D projections of optimization surfaces and trajectories, as well as high resolution second order gradient information for large networks.

 

Speaker: Raju Ram

Scalable Hyperparameter Optimization with Lazy Gaussian Processes

Abstract:

Most machine learning methods require careful selection of hyper-parameters in order to train a high performing model with good generalization abilities. Hence, several automatic selection algorithms have been introduced to overcome tedious manual (try anderror) tuning of these parameters. Due to its very high sample efficiency, Bayesian Optimization over a Gaussian Processes modeling of the parameter space has become the method of choice. Unfortunately, this approach suffers from a cubic compute complexity due to underlying Cholesky factorization, which makes it very hard to be scaled beyond a small number of sampling steps. In this talk, we present a novel, highly accurate approximation of the underlying Gaussian Process.

Reducing its computational complexity from cubic to quadratic allows an efficient strong scaling of Bayesian Optimization while outperforming the previous approach regarding optimization accuracy. First experiments show speedups of a factor of 162 in single node and further speed up by a factor of 5 in a parallel environment.

The seminar »KL-Regelungstechnik« (Kaiserslautern – Control Theory and Control Engineering) is organized by our department as well as several research groups of the TU Kaiserslautern:

  • Technomathematics (Dep. of Mathematics)
  • Mechatronics in Mechenical and Automotive Engineering (Dep. of Mechanical and Process Engineering)
  • Automation Control (Dep. of Electrical and Computer Engineering)
  • Electromobility (Dep. of Electrical and Computer Engineering)

The seminar takes place at the ITWM every 1st Tuesday of a month (besides holidays and summer break). Aims are broadening of experiences and exchange of scientific views – also beyond the organizing groups.

Typical subjects of talks are:

  • ongoing or recently finished graduations and doctoral theses
  • current research and projects

The topics vary from mathematical methods to technical implementations. Usually, the talks present research results. However, some show open issues for brainstorming and inputs from the audience.

The seminar »KL-Regelungstechnik« (Kaiserslautern – Control Theory and Control Engineering) is organized by our department as well as several research groups of the TU Kaiserslautern:

  • Technomathematics (Dep. of Mathematics)
  • Mechatronics in Mechenical and Automotive Engineering (Dep. of Mechanical and Process Engineering)
  • Automation Control (Dep. of Electrical and Computer Engineering)
  • Electromobility (Dep. of Electrical and Computer Engineering)

The seminar takes place at the ITWM every 1st Tuesday of a month (besides holidays and summer break). Aims are broadening of experiences and exchange of scientific views – also beyond the organizing groups.

Typical subjects of talks are:

  • ongoing or recently finished graduations and doctoral theses
  • current research and projects

The topics vary from mathematical methods to technical implementations. Usually, the talks present research results. However, some show open issues for brainstorming and inputs from the audience.

The seminar »KL-Regelungstechnik« (Kaiserslautern – Control Theory and Control Engineering) is organized by our department as well as several research groups of the TU Kaiserslautern:

  • Technomathematics (Dep. of Mathematics)
  • Mechatronics in Mechenical and Automotive Engineering (Dep. of Mechanical and Process Engineering)
  • Automation Control (Dep. of Electrical and Computer Engineering)
  • Electromobility (Dep. of Electrical and Computer Engineering)

The seminar takes place at the ITWM every 1st Tuesday of a month (besides holidays and summer break). Aims are broadening of experiences and exchange of scientific views – also beyond the organizing groups.

Typical subjects of talks are:

  • ongoing or recently finished graduations and doctoral theses
  • current research and projects

The topics vary from mathematical methods to technical implementations. Usually, the talks present research results. However, some show open issues for brainstorming and inputs from the audience.