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Can We Utilize Pre-trained Language Models within Causal Discovery Algorithms?
Scaling laws have allowed Pre-trained Language Models (PLMs) into the field of causal reasoning.
Geometrically Aligned Transfer Encoder for Inductive Transfer in Regression Tasks
Transfer learning is a crucial technique for handling a small amount of data that is potentially related to other abundant data.
Gradient Surgery for One-shot Unlearning on Generative Model
Recent regulation on right-to-be-forgotten emerges tons of interest in unlearning pre-trained machine learning models.
Semi-supervised regression with skewed data via adversarially forcing the distribution of predicted values
We assume the existence of enough unlabeled data that follow the true distribution, and that the true distribution can be roughly estimated from domain knowledge or a few samples.
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