3 citations · 11 across the 9 of their papers we have counts for
9 papers
Behavior Cloning is Not All You Need: The Optimality of On-Policy Distillation for Noisy Expert Feedback
Ved Sriraman, Peihan Liu, Daniel Hsu +1
Imitation Learning is a natural framework for learning in sequential decision-making systems and has emerged as the dominant paradigm through which we understand language model tra…
Privately Fine-Tuned LLMs Preserve Temporal Dynamics in Tabular Data
Lucas Rosenblatt, Peihan Liu, Ryan McKenna +1
Research on differentially private synthetic tabular data has largely focused on independent and identically distributed rows where each record corresponds to a unique individual.…
Convex Relaxation for Solving Large-Margin Classifiers in Hyperbolic Space
Sheng Yang, Peihan Liu, Cengiz Pehlevan
Hyperbolic spaces have increasingly been recognized for their outstanding performance in handling data with inherent hierarchical structures compared to their Euclidean counterpart…
Safeguarding Data in Multimodal AI: A Differentially Private Approach to CLIP Training
Alyssa Huang, Peihan Liu, Ryumei Nakada +2
The surge in multimodal AI's success has sparked concerns over data privacy in vision-and-language tasks. While CLIP has revolutionized multimodal learning through joint training o…
Improving Adversarial Transferability with Scheduled Step Size and Dual Example
Zeliang Zhang, Peihan Liu, Xiaosen Wang +1
Deep neural networks are widely known to be vulnerable to adversarial examples, especially showing significantly poor performance on adversarial examples generated under the white-…
How Robust is your Fair Model? Exploring the Robustness of Diverse Fairness Strategies
Edward Small, Wei Shao, Zeliang Zhang +4
With the introduction of machine learning in high-stakes decision making, ensuring algorithmic fairness has become an increasingly important problem to solve. In response to this,…
Polycyclic Codes Associated with Trinomials: Good Codes and Open Questions
Nuh Aydin, Peihan Liu, Bryan Yoshino
Polycyclic codes are a generalization of cyclic and constacyclic codes. Even though they have been known since 1972 and received some attention more recently, there have not been m…
Good Classical and Quantum Codes from Multi-Twisted Codes
Nuh Aydin, Thomas Guidotti, Peihan Liu
Multi-twisted (MT) codes were introduced as a generalization of quasi-twisted (QT) codes. QT codes have been known to contain many good codes. In this work, we show that codes with…
New Linear Codes as Quasi-Twisted Codes from Long Constacyclic Codes
Nuh Aydin, Thomas Guidotti, Peihan Liu
One of the most important and challenging problems in coding theory is to determine the optimal values of the parameters of a linear code and to explicitly construct codes with opt…