4 papers · 1 filter
Analyzing Political Text at Scale with Online Tensor LDA
Sara Kangaslahti, Danny Ebanks, Jean Kossaifi +3
This paper proposes a topic modeling method that scales linearly to billions of documents. We make three core contributions: i) we present a topic modeling method, Tensor Latent Di…
A Text-guided Protein Design Framework
Shengchao Liu, Yanjing Li, Zhuoxinran Li +10
Current AI-assisted protein design mainly utilizes protein sequential and structural information. Meanwhile, there exists tremendous knowledge curated by humans in the text format…
PerAda: Parameter-Efficient Federated Learning Personalization with Generalization Guarantees
Chulin Xie, De-An Huang, Wenda Chu +4
Personalized Federated Learning (pFL) has emerged as a promising solution to tackle data heterogeneity across clients in FL. However, existing pFL methods either (1) introduce high…
Neural Operator: Learning Maps Between Function Spaces
Nikola Kovachki, Zongyi Li, Burigede Liu +4
The classical development of neural networks has primarily focused on learning mappings between finite dimensional Euclidean spaces or finite sets. We propose a generalization of n…