Poster Session

Niklas Breustedt
TU Braunschweig, Germany

Unrolling versus bilevel optimization in the context of learning variational models

Styliani Kampezidou
Georgia Institute of Technology, USA

Online Adaptive Learning in Energy Trading Stackelberg Games with Time-Coupling Constraints

An energy trading mechanism is proposed between a selfish energy broker (aggregator) and her selfish energy customers (prosumers). The proposed design is a Stackelberg game where the aggregator trades energy bidirectionally between the prosumers and the wholesale electricity market for profit. For the purpose of satisfying the prosumers' desired energy consumption, time-coupling constraints are introduced. The described game does not admit closed form equilibrium strategies and therefore an online adaptive learning algorithm is proposed to mitigate this challenge. The latter is scalable with the number of prosumers and does not require explicit knowledge of the prosumers' decision-making mechanisms. Experimental results that utilize real-world data from the California market are provided to demonstrate the performance of the proposed approach.

Iosif Lytras
University of Edinburgh, United Kingdom

Taming neural networks with TUSLA: Non-convex learning via adaptive stochastic gradient Langevin algorithms

Joint work with Attila Lovas, Miklós Rásonyi and Sotirios Sabanis

Arxiv Url : arxiv.org/pdf/2006.14514.pdf

Johannes Müller
Max Planck Institute for Mathematics in the Sciences, Germany

The geometry of discounted stationary distributions of Markov decision processes

Oren Neumann
Goethe University Frankfurt am Main, Germany

Investment Vs. reward in competitive games

Maximilian Steffen
Universität Hamburg, Germany

PAC-Bayesian Estimation for High-Dimensional Multi-Index Regression with Unknown Active Dimension

David Szeghy
Eötvös Loránd University (ELTE), Hungary

Adversarial Perturbation Stability of the Layered Group Basis Pursuit

Hanna Tseran
MPI for Mathematics in the Sciences, Germany

On the Expected Complexity of Maxout Networks

Jesse van Oostrum
Hamburg University of Technology, Germany

Parametrisation Independence of the Natural Gradient in Overparametrised Systems

Csongor-Huba Varady
Max Planck Institute for Mathematics in the Sciences (MiS) in Leipzig., Germany

Natural Reweighted Wake Sleep for Convolutional Networks

Xiaoyu Wang
University of Cambridge, United Kingdom

Lifted Bregman Networks

Chia Zargeh
University of Sao Paulo, Brazil

Applications of associative algebras in machine learning