Poster Session
Abstract
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