1. Deep Ordinal Regression Based on Data Relationship for Small Datasets
使用triplet增加数据，从而在小数据集上实现ordinal regression.
2. Image Scoring: Patch Based CNN Model for Small or Medium Dataset
提出一种oversampling的技术，同时考虑整个image和local patches.
3. A neural network based model to analyze rice parboiling process with small dataset
在小数据集上研究大米加热过程？用到了multivariate regression.
4. A Constrained Deep Neural Network for Ordinal Regression
提出的方法在大、小数据集上都可以用
5. Efficient Sublinear-Regret Algorithms for Online Sparse Linear Regression with Limited Observation
Online regression里通常只能make a prediction with a limited number of features
6. A strategy to apply machine learning to small datasets in materials science
里面用到了kernel ridge regression
7. Optimal Bayesian Transfer Regression
用transfer learning解决数据量少的问题
8. Human Guided Linear Regression with Feature-Level Constraints
通过人为识别特征，解决缺少labeled data的情况
9. Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance
通过半监督学习来解决缺少labeled data的问题
