Search Results for author:
Found 3 papers, 1 papers with code
SBoRA: Low-Rank Adaptation with Regional Weight Updates
This paper introduces Standard Basis LoRA (SBoRA), a novel parameter-efficient fine-tuning approach for Large Language Models that builds upon the pioneering works of Low-Rank Adaptation (LoRA) and Orthogonal Adaptation.
Interpretable Latent Variables in Deep State Space Models
We introduce a new version of deep state-space models (DSSMs) that combines a recurrent neural network with a state-space framework to forecast time series data.
A News-based Machine Learning Model for Adaptive Asset Pricing
The paper proposes a new asset pricing model -- the News Embedding UMAP Selection (NEUS) model, to explain and predict the stock returns based on the financial news.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
