11 citations · 18 across the 7 of their papers we have counts for
9 papers
Subgroup Discovery with the Cox Model
Zachary Izzo, Iain Melvin
We study the problem of subgroup discovery for survival analysis, where the goal is to find an interpretable subset of the data on which a Cox model is highly accurate. Our work is…
To Err Is Human: Systematic Quantification of Errors in Published AI Papers via LLM Analysis
Federico Bianchi, Yongchan Kwon, Zachary Izzo +2
How many mistakes do published AI papers contain? Peer-reviewed publications form the foundation upon which new research and knowledge are built. Errors that persist in the literat…
Quantitative Bounds for Length Generalization in Transformers
Zachary Izzo, Eshaan Nichani, Jason D. Lee
We study the problem of length generalization (LG) in transformers: the ability of a model trained on shorter sequences to maintain performance when evaluated on much longer, previ…
Group Relative Augmentation for Data Efficient Action Detection
Deep Anil Patel, Iain Melvin, Zachary Izzo +1
Adapting large Video-Language Models (VLMs) for action detection using only a few examples poses challenges like overfitting and the granularity mismatch between scene-level pre-tr…
Solving Inverse Problems via Diffusion-Based Priors: An Approximation-Free Ensemble Sampling Approach
Haoxuan Chen, Yinuo Ren, Martin Renqiang Min +2
Diffusion models (DMs) have proven to be effective in modeling high-dimensional distributions, leading to their widespread adoption for representing complex priors in Bayesian inve…
Provable Membership Inference Privacy
Zachary Izzo, Jinsung Yoon, Sercan O. Arik +1
In applications involving sensitive data, such as finance and healthcare, the necessity for preserving data privacy can be a significant barrier to machine learning model developme…