3 papers
cs.LG2025
Preventing Model Collapse via Contraction-Conditioned Neural Filters
Zongjian Han, Yiran Liang, Ruiwen Wang +4
This paper presents a neural network filter method based on contraction operators to address model collapse in recursive training of generative models. Unlike \cite{xu2024probabili…
stat.ME2025
Reluctant Interaction Inference after Additive Modeling
Yiling Huang, Snigdha Panigrahi, Guo Yu +1
Additive models enjoy the flexibility of nonlinear models while still being readily understandable to humans. By contrast, other nonlinear models, which involve interactions betwee…
stat.ME2024
Inference with Randomized Regression Trees
Soham Bakshi, Yiling Huang, Snigdha Panigrahi +1
Regression trees are a popular machine learning algorithm that fit piecewise constant models by recursively partitioning the predictor space. This paper focuses on statistical infe…