The following pages link to SVMstruct (Q16262):
Displaying 22 items.
- Learning multiple metrics for ranking (Q352075) (← links)
- Multilabel classification with meta-level features in a learning-to-rank framework (Q439034) (← links)
- The risk of trivial solutions in bipartite top ranking (Q669314) (← links)
- MLRank: multi-correlation learning to rank for image annotation (Q888565) (← links)
- DEARank: a data-envelopment-analysis-based ranking method (Q890309) (← links)
- Query-dependent ranking and its asymptotic properties (Q1722064) (← links)
- Cutting-plane training of structural SVMs (Q1959520) (← links)
- Large scale image annotation: learning to rank with joint word-image embeddings (Q1959605) (← links)
- Learning to rank on graphs (Q1959630) (← links)
- Optimizing predictive precision in imbalanced datasets for actionable revenue change prediction (Q2184072) (← links)
- Structured learning of binary codes with column generation for optimizing ranking measures (Q2193865) (← links)
- Calibration and regret bounds for order-preserving surrogate losses in learning to rank (Q2251435) (← links)
- Efficient regularized least-squares algorithms for conditional ranking on relational data (Q2251443) (← links)
- Sequential event prediction (Q2251444) (← links)
- Optimal threshold analysis of segmentation methods for identifying target customers (Q2462131) (← links)
- The bane of skew. Uncertain ranks and unrepresentative precision (Q2512893) (← links)
- Active Set Iteration Method for New L2 Soft Margin Support Vector Machine (Q3063130) (← links)
- Learning to Rank for Information Retrieval (Q3577032) (← links)
- (Q4637020) (← links)
- Analysis of <i>k</i>-partite ranking algorithm in area under the receiver operating characteristic curve criterion (Q5028602) (← links)
- Support Vector Algorithms for Optimizing the Partial Area under the ROC Curve (Q5380824) (← links)
- Listwise approaches based on feature ranking discovery (Q5964249) (← links)
