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Found 5 papers, 0 papers with code
Transfer learning via Regularized Linear Discriminant Analysis
In this paper, we present novel transfer learning methods via regularized random-effects linear discriminant analysis, where the discriminant direction is estimated as a weighted combination of ridge estimates obtained from both the target and source models.
Semisupervised score based matching algorithm to evaluate the effect of public health interventions
We proposed a novel one-to-one matching algorithm based on a quadratic score function $S_{\beta}(x_i, x_j)= \beta^T (x_i-x_j)(x_i-x_j)^T \beta$.
Bias of AI-Generated Content: An Examination of News Produced by Large Language Models
We then apply each examined LLM to generate news content with headlines of these news articles as prompts, and evaluate the gender and racial biases of the AIGC produced by the LLM by comparing the AIGC and the original news articles.
Proactive Resource Request for Disaster Response: A Deep Learning-based Optimization Model
Prior resource management research for disaster response overlooks the problem of deciding optimal quantities of resources requested by a local agency.
Transfer Learning with Random Coefficient Ridge Regression
This paper considers estimation and prediction of random coefficient ridge regression in the setting of transfer learning, where in addition to observations from the target model, source samples from different but possibly related regression models are available.
