1.
Approach to Eliminating Morbid Samples in Forward Neural Networks
前馈神经网络病态学习样本剔除方法
2.
Effect of Neural Network Learning Patterns on Forecast of Tyre Curing Temperature
神经网络学习样本对轮胎硫化温度预测的影响
3.
Analysis of Decision Rules in the Presence Of Classification Errors of the Learning Sample;
学习样本存在分类错误时的决策判据分析
4.
Partitioning machine learning sample set using similarity to mean vector
基于均矢量相似性的机器学习样本集划分
5.
Experiments show that the learned metrics can be used to significantly improve image retrieval performance.
试验结果表明，该方法能在学习样本极少的情况下提高检索的性能。
6.
The Foundation of Statistical Learning Theory with Rough Samples;
基于粗糙样本的统计学习理论的基础
7.
An incremental learning algorithm for multi-class sample
实现兼类样本类增量学习的一种算法
8.
The Key Theorem of Learning Theory on Rough Random Samples;
基于粗糙随机样本的学习理论的关键定理
9.
Some Studies of Learning Theory about Samples Corrupted by Noise on Credibility Space;
可信性空间上样本受噪声影响的学习理论研究
10.
Some Theoretical Studies on Learning Theory with Samples Corrupted by Zero-expect Noise;
零均值噪声样本下学习理论的若干理论研究
11.
The Key Theirem of Statistical Learning Theory about Fuzzy Examples;
基于模糊样本的统计学习理论关键定理
12.
An Algorithm for Representative Sampling Based on Incremental Learning;
一种基于增量学习的典型样本选取方法
13.
The Theoretical Foundations of Statistical Learning Theory of Birough Samples
基于双重粗糙样本的统计学习理论的理论基础
14.
Small Sample Incremental Biased Learning Algorithm for Sketch Retrieval
面向草图检索的小样本增量有偏学习算法
15.
Key Theorem of Learning Theory Based on Rough Random Samples
基于粗糙随机样本学习理论的关键定理
16.
Statistical learning theory of complex samples on Sugeno measure space
Sugeno测度空间基于复样本的统计学习理论
17.
Key theorem of learning theory about complex g_λ samples corrupted by noise
受噪声影响的复g_λ样本的学习理论的关键定理
18.
follow the example of sb.
学（习）某人的榜样