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Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Optimal semi-supervised subsampling via predictive inference
预测推理 最优 半监督子采样
2023/4/26
In big data era, subsampling or sub-data selection techniques are often adopted to extract a fraction of informative individuals from the massive data. Existing subsampling algorithms focus mainly on ...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Fusion of Supervised Learning and Reinforcement Learning for Dynamic Treatment Recommendation
监督学习 强化学习 融合 动态治疗推荐
2023/5/5
Electronic health records (EHR) have provided a great opportunity to exploit personalized health data to optimize clinical decision making and achieve personalized treatment recommendation. In this ta...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars： Fusion of Supervised Learning and Reinforcement Learning for Dynamic Treatment Recommendation
监督学习 强化学习 融合 动态治疗推荐 电子健康记录
2023/5/6
Electronic health records (EHR) have provided a great opportunity to exploit personalized health data to optimize clinical decision making and achieve personalized treatment recommendation. In this ta...
SEMANTIC SEGMENTATION OF CONVOLUTIONAL NEURAL NETWORK FOR SUPERVISED CLASSIFICATION OF MULTISPECTRAL REMOTE SENSING
Semantic Segmentation Multi Spectral Remote Sensing Convolutional Neural Network U-net multi-scale image
2018/5/16
Semantic segmentation is a fundamental research in remote sensing image processing. Because of the complex maritime environment, the classification of roads, vegetation, buildings and water from remot...
A Method for Inferring Label Sampling Mechanisms in Semi-Supervised Learning
Inferring Label Sampling Mechanisms Semi-Supervised Learning
2015/8/21
We consider the situation in semi-supervised learning, where the “label sampling” mechanism stochastically depends on the true response (as well as potentially on the features). We suggest a method of...
Prediction by Supervised Principal Components
Gene expression Microarray Regression Survival analysis
2015/8/21
In regression problems where the number of predictors greatly exceeds the number of observations, conventional regression techniques may produce unsatisfactory results. We describe a technique called ...
In regression problems where the number of predictors greatly exceeds the number of observations, conventional regression techniques may produce unsatisfactory results. We describe a technique called ...
SUPERVISED AND UNSUPERVISED NEURAL MODELS FOR MULTISPECTRAL IMAGE CLASSIFICATION
Land Cover Classification Identification Algorithms Artificial_Intelligence Imagery Pixel Multispectral
2015/7/29
Competitive learning neural networks have been successfully used as unsupervised training methods. It provides a way to discover the
salient general features that can be used to classify a set of pa...
SERAPH: Semi-supervised Metric Learning Paradigm with Hyper Sparsity
Semi-supervised Metric Learning Paradigm Hyper Sparsity
2011/6/15
We consider the problem of learning a distance metric from a limited amount of pairwise information as effectively as possible. The proposed SERAPH (SEmi-supervised metRic leArning Paradigm with Hyper...
Genetic Classification of Populations using Supervised Learning
Genetic Classification Populations Supervised Learning
2011/1/5
There are many instances in genetics in which we wish to determine whether two candidate populations are distinguishable on the basis of their genetic structure. Examples include populations which are...
Safe Feature Elimination in Sparse Supervised Learning
Sparse classi cation sparse regression LASSO feature elimination
2010/12/16
We investigate fast methods that allow to quickly eliminate variables (features) in supervised
learning problems involving a convex loss function and a l1-norm penalty, leading to a potentially subst...
Supervised and Unsupervised Learning of Multidimensional Acoustic Categories
auditory categories supervised learning unsupervised learning nonspeech
2014/5/7
Learning to recognize the contrasts of a language-specific phonemic repertoire can be viewed as forming categories in a multidimensional psychophysical space. Research on the learning of distributiona...