An Introduction to Advanced Machine Learning : Meta Learning Algorithms, Applications and Promises

Promises and pitfalls of deep neural networks in neuroimaging-based psychiatric research

By promising more accurate diagnostics and individual treatment recommendations, deep neural networks and in particular convolutional neural networks have advanced to a powerful tool in medical imaging. Here, we first give an introduction into methodological key concepts and resulting methodological promises including representation and transfer learning, as well as modelling domain-specific priors. After reviewing recent applications within neuroimaging-based psychiatric research, such as the diagnosis of psychiatric diseases, delineation of disease subtypes, normative modeling, and the devel…

Modeling and Optimization Trade-off in Meta-learning

By searching for shared inductive biases across tasks, meta-learning promises to accelerate learning on novel tasks, but with the cost of solving a complex bilevel optimization problem. We introduce and rigorously define the trade-off between accurate modeling and optimization ease in meta-learning. At one end, classic meta-learning algorithms account for the structure of meta-learning but solve a complex optimization problem, while at the other end domain randomized search (otherwise known as joint training) ignores the structure of meta-learning and solves a single level optimization problem…

面向自适应XGBoost-神经网络集成的动态元学习

Dynamic Meta-Learning for Adaptive XGBoost-Neural Ensembles

本研究提出一种结合XGBoost与神经网络的自适应集成框架，借助元学习、不确定性量化及特征重要性融合实现动态模型调度，在多数据集上取得更优预测性能与可解释性。

用于早期精准脓毒症预测以改善患者预后的高级元集成机器学习模型

Advanced Meta-Ensemble Machine Learning Models for Early and Accurate Sepsis Prediction to Improve Patient Outcomes

针对传统脓毒症筛查工具的局限性，该研究提出基于随机森林、极端梯度提升、决策树的元集成机器学习模型用于脓毒症早期预测，其AUC-ROC达0.96，优于各单模型，可助力提升患者预后。

Text2Analysis：一个面向高级数据分析与模糊查询的表格问答基准

Text2Analysis: A Benchmark of Table Question Answering with Advanced Data Analysis and Unclear Queries

针对现有表格问答研究忽视高级分析与模糊查询的问题，构建了包含2249个查询-结果对、347个表格的Text2Analysis基准，并评估五个先进模型，验证了其挑战性。

用于高度非线性系统综合设计优化的先进物理信息神经算子：航空航天复合材料加工案例研究

An Advanced Physics-Informed Neural Operator for Comprehensive Design Optimization of Highly-Nonlinear Systems: An Aerospace Composites Processing Case Study

针对航空航天复合材料加工等强非线性、多输入函数系统，本文提出融合非线性解码器、课程学习与区域分解的先进物理信息 DeepONet，显著提升高维设计空间预测精度并支持零样本优化。