Pages that link to "Item:Q5959956"
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The following pages link to On the dual formulation of regularized linear systems with convex risks (Q5959956):
Displaying 16 items.
- Dual coordinate descent methods for logistic regression and maximum entropy models (Q413884) (← links)
- Regression tasks in machine learning via Fenchel duality (Q490215) (← links)
- Regularized learning in Banach spaces as an optimization problem: representer theorems (Q693135) (← links)
- Learning the coordinate gradients (Q695644) (← links)
- A new accelerated algorithm for ill-conditioned ridge regression problems (Q725822) (← links)
- Multi-kernel regularized classifiers (Q870343) (← links)
- An experimental comparison of cross-validation techniques for estimating the area under the ROC curve (Q901569) (← links)
- The complexity of primal-dual fixed point methods for ridge regression (Q1669015) (← links)
- Variant of greedy randomized Kaczmarz for ridge regression (Q2311776) (← links)
- Concentration of weakly dependent Banach-valued sums and applications to statistical learning methods (Q2325378) (← links)
- Theoretically optimal parameter choices for support vector regression machines with noisy input (Q2576617) (← links)
- Generalized semi-inner products with applications to regularized learning (Q2637940) (← links)
- Leave-One-Out Bounds for Kernel Methods (Q4816853) (← links)
- (Q5053232) (← links)
- (Q5405233) (← links)
- Accelerated proximal stochastic dual coordinate ascent for regularized loss minimization (Q5962715) (← links)
