ASSET

Presentation Abstract: Huge strides have made in the widespread adoption of autonomous and human-in-the-loop cyber-physical systems (CPS), partly fueled by dramatic improvements in learning-based techniques. An important aspect of such CPS applications is that they are safety-critical: any undesirable behavior by such systems can cause serious harm to human lives or property. The formal methods […]

ABSTRACT: I'll present research on using large language models (LLMs) to build explainable classifiers.   I will show off work from my PhD students and collaborators on several recent research directions: Image classification with explainable features  (https://arxiv.org/abs/2211.11158) Text classification with explainable features (work in progress) The importance of faithfulness in explanations (https://arxiv.org/abs/2209.11326) (Time permitting) A […]

Abstract: Machine learning algorithms are increasingly used in conjunction with optimization to guide decision making. A key challenge is aligning the machine learning loss with the decision-making loss. Existing solutions have limited flexibility and/or scale poorly to large datasets. We propose a principled decision-aware learning algorithm that uses a Taylor expansion of the optimal decision […]