The following pages link to SVMlight (Q16263):
Displaying 50 items.
- Classifying real-world data with the \(DD\alpha\)-procedure (Q2418399) (← links)
- About the non-convex optimization problem induced by non-positive semidefinite kernel learning (Q2442765) (← links)
- Optimized fixed-size kernel models for large data sets (Q2445599) (← links)
- Optimal threshold analysis of segmentation methods for identifying target customers (Q2462131) (← links)
- An improved gradient projection-based decomposition technique for support vector machines (Q2468369) (← links)
- Non-parametric regression methods (Q2468374) (← links)
- New algorithms for singly linearly constrained quadratic programs subject to lower and upper bounds (Q2492668) (← links)
- Confidence-based classifier design (Q2495916) (← links)
- Prediction by support vector machines and analysis by \(Z\)-score of poly-\(L\)-proline type II conformation based on local sequence (Q2500273) (← links)
- Predicting \(O\)-glycosylation sites in mammalian proteins by using SVMs (Q2500380) (← links)
- Efficient optimization of support vector machine learning parameters for unbalanced datasets (Q2503014) (← links)
- A novel and quick SVM-based multi-class classifier (Q2507100) (← links)
- A bio-basis function neural network for protein peptide cleavage activity characterisation (Q2507296) (← links)
- Rank sum method for related gene selection and its application to tumor diagnosis (Q2568916) (← links)
- Alternating direction method of multipliers for \(\ell_{1}\)-\(\ell_{2}\)-regularized logistic regression model (Q2630840) (← links)
- New smoothing SVM algorithm with tight error bound and efficient reduced techniques (Q2636609) (← links)
- Two-level \(k\)-means clustering algorithm for \(k\)-\(\tau \) relationship establishment and linear-time classification (Q2654244) (← links)
- Incremental and decremental fuzzy bounded twin support vector machine (Q2663581) (← links)
- (Q2740522) (← links)
- Estimating the support of a high-dimensional distribution (Q2746407) (← links)
- An introduction to support vector machines and other kernel-based learning methods. (Q2755103) (← links)
- Support vector machine active learning with applications to text classification (Q2782269) (← links)
- SVMTorch: Support vector machines for large-scale regression problems. (Q2782275) (← links)
- Supervised Learning by Support Vector Machines (Q2789826) (← links)
- A unified view on multi-class support vector classification (Q2810837) (← links)
- New SDP models for protein homology detection with semi-supervised SVM (Q2841145) (← links)
- Bundle methods for regularized risk minimization (Q2896030) (← links)
- Maximum relative margin and data-dependent regularization (Q2896053) (← links)
- Training and testing low-degree polynomial data mappings via linear SVM (Q2896086) (← links)
- Dual averaging methods for regularized stochastic learning and online optimization (Q2896156) (← links)
- A comparison of optimization methods and software for large-scale L1-regularized linear classifi\-cation (Q2896183) (← links)
- Decision forests: a unified framework for classification, regression, density estimation, manifold learning and semi-supervised learning (Q2904219) (← links)
- Solving a Multigroup Mixed-Integer Programming-Based Constrained Discrimination Model (Q2940542) (← links)
- Active Set Iteration Method for New L2 Soft Margin Support Vector Machine (Q3063130) (← links)
- Large-Scale Training of SVMs with Automata Kernels (Q3073616) (← links)
- (Q3093201) (← links)
- (Q3093211) (← links)
- (Q3093253) (← links)
- (Q3093278) (← links)
- (Q3093310) (← links)
- (Q3093324) (← links)
- (Q3093368) (← links)
- (Q3093391) (← links)
- (Q3093400) (← links)
- (Q3093401) (← links)
- (Q3093402) (← links)
- 10.1162/15324430260185600 (Q3148139) (← links)
- 10.1162/15324430260185619 (Q3148140) (← links)
- 10.1162/15324430260185628 (Q3148141) (← links)
- (Q3174027) (← links)
