8 citations · 18 across the 4 of their papers we have counts for
5 papers
The Boltzmann Policy Distribution: Accounting for Systematic Suboptimality in Human Models
Cassidy Laidlaw, Anca Dragan
Models of human behavior for prediction and collaboration tend to fall into two categories: ones that learn from large amounts of data via imitation learning, and ones that assume…
Uncertain Decisions Facilitate Better Preference Learning
Cassidy Laidlaw, Stuart Russell
Existing observational approaches for learning human preferences, such as inverse reinforcement learning, usually make strong assumptions about the observability of the human's env…
Playing it Safe: Adversarial Robustness with an Abstain Option
Cassidy Laidlaw, Soheil Feizi
We explore adversarial robustness in the setting in which it is acceptable for a classifier to abstain---that is, output no class---on adversarial examples. Adversarial examples ar…
Functional Adversarial Attacks
Cassidy Laidlaw, Soheil Feizi
We propose functional adversarial attacks, a novel class of threat models for crafting adversarial examples to fool machine learning models. Unlike a standard -ball threat…
Capture, Learning, and Synthesis of 3D Speaking Styles
Daniel Cudeiro, Timo Bolkart, Cassidy Laidlaw +2
Audio-driven 3D facial animation has been widely explored, but achieving realistic, human-like performance is still unsolved. This is due to the lack of available 3D datasets, mode…