1
Nonparametric Control Koopman Operators
非参数化Koopman算子在控制领域的突破，为非线性系统建模与控制提供全新视角
arXiv:2405.07312v5 Announce Type: replace-cross Abstract: This paper presents a novel Koopman composition operator representation framework for contro…
2
Structured Nonparametric Variational Inference for Dependent Latent Modeling
提出结构化非参数变分推断新方法，有效建模依赖潜在变量，突破传统变分推断局限。
arXiv:2606.15458v1 Announce Type: cross Abstract: Variational inference (VI) is a core engine of modern AI, enabling scalable approximate Bayesian lea…
3
Nonparametric LLM Evaluation from Preference Data
非参数方法评估LLM性能，突破参数假设限制，提供可靠的不确定性量化
arXiv:2601.21816v2 Announce Type: replace Abstract: Evaluating the performance of large language models (LLMs) from human preference data is crucial f…
4
SMART Fine-tuning Factor Augmented Neural Lasso
提出SMART框架，将预训练模型融入高维非参数变量选择，为微调提供理论基础。
arXiv:2604.12288v2 Announce Type: replace-cross Abstract: Fine-tuning is a widely used strategy for adapting pre-trained models to new tasks, yet its …
5
Kernelized Advantage Estimation: From Nonparametric Statistics to LLM Reasoning
该论文提出Kernelized Advantage Estimation方法，从非参数统计视角优化LLM推理，为强化学习提供新思路。
arXiv:2604.28005v2 Announce Type: replace Abstract: Recent advances in large language models (LLMs) have increasingly relied on reinforcement learning…
6
Density Estimation via Binless Multidimensional Integration
新方法BMTI通过无箱多维积分实现非参数密度估计，数据高效且鲁棒。
arXiv:2407.08094v3 Announce Type: replace-cross Abstract: We introduce the Binless Multidimensional Thermodynamic Integration (BMTI) method for nonpar…