Yuan Luo

Open-Set Recognition with Gaussian Mixture Variational Autoencoders

2020 · arXiv (Cornell University)

In inference, open-set classification is to either classify a sample into a known class from training or reject it as an unknown class. Existing deep open-set classifiers train explicit closed-set classifiers, in some cases disjointly …

A comparative study of pretrained language models for long clinical text

2022 · Journal of the American Medical Informatics Association

OBJECTIVE: Clinical knowledge-enriched transformer models (eg, ClinicalBERT) have state-of-the-art results on clinical natural language processing (NLP) tasks. One of the core limitations of these transformer models is the substantial memory consumption due to their full …

Rethinking Domain Generalization: Discriminability and Generalizability

2023 · arXiv (Cornell University)

Domain generalization(DG) endeavors to develop robust models that possess strong generalizability while preserving excellent discriminability. Nonetheless, pivotal DG techniques tend to improve the feature generalizability by learning domain-invariant representations, inadvertently overlooking the feature discriminability. On …

Privacy-Preserving UCB Decision Process Verification via zk-SNARKs

2024 · arXiv (Cornell University)

With the increasingly widespread application of machine learning, how to strike a balance between protecting the privacy of data and algorithm parameters and ensuring the verifiability of machine learning has always been a challenge. This …