Description
frEnbis Invited session
Our research addresses the industrial challenge of minimising production costs in an undiscounted, continuing, partially observable setting. We argue that existing state-of-the-art reinforcement learning algorithms are unsuitable for this context. We introduce Clipped Horizon Average Reward (CHAR), a method tailored for undiscounted optimisation. CHAR is an extension applicable to any...
The aim of AI based on machine learning is to generalize information about individuals to an entire population. And yet...
- Can an AI leak information about its training data?
- Since the answer to the first question is yes, what kind of information can it leak?
- How can it be attacked to retrieve this information?
To emphasize AI vulnerability issues, Direction Générale de l’Armement...
In this presentation, we provide an overview of deep learning applications in electricity markets, focusing on several key areas of forecasting. First, we discuss state-of-the-art methods for forecasting electricity demand, including Generalised Additive Models (GAMs), which inspired the work that follows. Second, we look at multi-resolution forecasting, which uses data at high- and...