The following pages link to (Q3174144):
Displaying 30 items.
- Significance analysis of high-dimensional, low-sample size partially labeled data (Q286481) (← links)
- Feature selection in the Laplacian support vector machine (Q452629) (← links)
- Bayesian semi-supervised learning with support vector machine (Q537464) (← links)
- Multiclass classification with potential function rules: margin distribution and generalization (Q645885) (← links)
- A second order cone programming approach for semi-supervised learning (Q898241) (← links)
- Generalization performance of graph-based semi-supervised classification (Q1047879) (← links)
- Semi-supervised classification method through oversampling and common hidden space (Q1615661) (← links)
- On the prediction loss of the Lasso in the partially labeled setting (Q1616320) (← links)
- Maximum margin semi-supervised learning with irrelevant data (Q1669167) (← links)
- DC programming and DCA: thirty years of developments (Q1749443) (← links)
- Semi-supervised learning based on high density region estimation (Q1784700) (← links)
- A predictive deviance criterion for selecting a generative model in semi-supervised classification (Q1800092) (← links)
- Explicit connections between longitudinal data analysis and kernel machines (Q1952003) (← links)
- Margin-based semi-supervised learning using Apollonius circle (Q1997261) (← links)
- Robust semi-supervised least squares classification by implicit constraints (Q2290315) (← links)
- Conditional probability estimation based classification with class label missing at random (Q2293539) (← links)
- A survey on semi-supervised learning (Q2303675) (← links)
- Semi-supervised inference: general theory and estimation of means (Q2328051) (← links)
- Variable selection for multicategory SVM via adaptive sup-norm regularization (Q2426830) (← links)
- A sparse large margin semi-supervised learning method (Q2511744) (← links)
- An auto-adjustable semi-supervised self-training algorithm (Q2633260) (← links)
- On efficient large margin semisupervised learning: method and theory (Q2880894) (← links)
- Effective Active Learning Strategies for the Use of Large-Margin Classifiers in Semantic Annotation: An Optimal Parameter Discovery Perspective (Q2940534) (← links)
- (Q4614127) (← links)
- An iterative algorithm to learn from positive and unlabeled examples (Q5066784) (← links)
- (Q6121725) (← links)
- Collaborative Multilabel Classification (Q6165279) (← links)
- A General M-estimation Theory in Semi-Supervised Framework (Q6567902) (← links)
- On regression and classification with possibly missing response variables in the data (Q6594919) (← links)
- Semi-supervised inference for nonparametric logistic regression (Q6625795) (← links)
