Cassidy Laidlaw

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 20

Top Topics

Malicious Attacks

Decision Theory

Preference Learning

Top Venues

Publications

Lauren H. Cooke, Harvey Klyne, Edwin Zhang, Cassidy Laidlaw, Milind Tambe, Finale Doshi-Velez
Toward Computationally Efficient Inverse Reinforcement Learning via Reward Shaping. Tiny Papers @ ICLR (2024)
Cassidy Laidlaw, Banghua Zhu, Stuart Russell, Anca D. Dragan
The Effective Horizon Explains Deep RL Performance in Stochastic Environments. ICLR (2024)
Cassidy Laidlaw, Shivam Singhal, Anca D. Dragan
Preventing Reward Hacking with Occupancy Measure Regularization. CoRR (2024)
Anand Siththaranjan, Cassidy Laidlaw, Dylan Hadfield-Menell
Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF. ICLR (2024)
Anand Siththaranjan, Cassidy Laidlaw, Dylan Hadfield-Menell
Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF. CoRR (2023)
Cassidy Laidlaw, Banghua Zhu, Stuart Russell, Anca D. Dragan
The Effective Horizon Explains Deep RL Performance in Stochastic Environments. CoRR (2023)
Cassidy Laidlaw, Stuart J. Russell, Anca D. Dragan
Bridging RL Theory and Practice with the Effective Horizon. NeurIPS (2023)
Cassidy Laidlaw, Stuart Russell, Anca D. Dragan
Bridging RL Theory and Practice with the Effective Horizon. CoRR (2023)
Lauren H. Cooke, Harvey Klyne, Edwin Zhang, Cassidy Laidlaw, Milind Tambe, Finale Doshi-Velez
Toward Computationally Efficient Inverse Reinforcement Learning via Reward Shaping. CoRR (2023)
Cassidy Laidlaw, Anca D. Dragan
The Boltzmann Policy Distribution: Accounting for Systematic Suboptimality in Human Models. CoRR (2022)
Cassidy Laidlaw, Anca D. Dragan
The Boltzmann Policy Distribution: Accounting for Systematic Suboptimality in Human Models. ICLR (2022)
Cassidy Laidlaw, Stuart Russell
Uncertain Decisions Facilitate Better Preference Learning. NeurIPS (2021)
Cassidy Laidlaw, Sahil Singla, Soheil Feizi
Perceptual Adversarial Robustness: Defense Against Unseen Threat Models. ICLR (2021)
Cassidy Laidlaw, Stuart Russell
Learning the Preferences of Uncertain Humans with Inverse Decision Theory. CoRR (2021)
Cassidy Laidlaw, Sahil Singla, Soheil Feizi
Perceptual Adversarial Robustness: Defense Against Unseen Threat Models. CoRR (2020)
Daniel Cudeiro, Timo Bolkart, Cassidy Laidlaw, Anurag Ranjan, Michael J. Black
Capture, Learning, and Synthesis of 3D Speaking Styles. CoRR (2019)
Cassidy Laidlaw, Soheil Feizi
Functional Adversarial Attacks. CoRR (2019)
Daniel Cudeiro, Timo Bolkart, Cassidy Laidlaw, Anurag Ranjan, Michael J. Black
Capture, Learning, and Synthesis of 3D Speaking Styles. CVPR (2019)
Cassidy Laidlaw, Soheil Feizi
Playing it Safe: Adversarial Robustness with an Abstain Option. CoRR (2019)
Cassidy Laidlaw, Soheil Feizi
Functional Adversarial Attacks. NeurIPS (2019)