Adversarial Machine Learning: from Models to Practice

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Game-Focused Learning in Cooperative and Non-Cooperative Games

In many real-world interactions between strategic agents, decision theoretic reasoning is complicated by a lack of understanding of the preferences or utility functions of the agents in the interaction. If we could solve the learning problem optimally, the models could be plugged in to well-developed tools from game theory. However, learning perfect models is rarely possible, requiring the learned model to reflect its use in strategic reasoning. In this talk, I discuss two different domains where these...

Data as Collectively Generated Pattern: Making Sense of Data Ownership

Data ownership is genuine power. Who should hold that...