Pages that link to "Item:Q633112"
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The following pages link to Pegasos: primal estimated sub-gradient solver for SVM (Q633112):
Displaying 50 items.
- Algorithms for stochastic optimization with function or expectation constraints (Q2181600) (← links)
- Image annotation by propagating labels from semantic neighbourhoods (Q2187434) (← links)
- Bridging the gap between constant step size stochastic gradient descent and Markov chains (Q2196224) (← links)
- Insensitive stochastic gradient twin support vector machines for large scale problems (Q2198233) (← links)
- An efficient method for clustered multi-metric learning (Q2200672) (← links)
- Kernel-based online regression with canal loss (Q2242215) (← links)
- Developing an online general type-2 fuzzy classifier using evolving type-1 rules (Q2302784) (← links)
- Decentralized hierarchical constrained convex optimization (Q2303528) (← links)
- Fast and strong convergence of online learning algorithms (Q2305549) (← links)
- Hyper-parameter optimization for support vector machines using stochastic gradient descent and dual coordinate descent (Q2308188) (← links)
- The incremental subgradient methods on distributed estimations in-network (Q2335919) (← links)
- An efficient primal dual prox method for non-smooth optimization (Q2339936) (← links)
- Premise selection for mathematics by corpus analysis and kernel methods (Q2352489) (← links)
- Incremental accelerated gradient methods for SVM classification: study of the constrained approach (Q2355191) (← links)
- Stochastic subgradient descent method for large-scale robust chance-constrained support vector machines (Q2359408) (← links)
- Binary vectors for fast distance and similarity estimation (Q2362826) (← links)
- An optimal subgradient algorithm with subspace search for costly convex optimization problems (Q2415906) (← links)
- A fast SVD-hidden-nodes based extreme learning machine for large-scale data analytics (Q2418132) (← links)
- Image classification with the Fisher vector: theory and practice (Q2450399) (← links)
- Subgradient-based neural network for nonconvex optimization problems in support vector machines with indefinite kernels (Q2515282) (← links)
- New smoothing SVM algorithm with tight error bound and efficient reduced techniques (Q2636609) (← links)
- Online strongly convex optimization with unknown delays (Q2673315) (← links)
- Improving kernel online learning with a snapshot memory (Q2673322) (← links)
- Spectral projected subgradient method for nonsmooth convex optimization problems (Q2700023) (← links)
- Coordinate descent with arbitrary sampling I: algorithms and complexity<sup>†</sup> (Q2829565) (← links)
- Block Stochastic Gradient Iteration for Convex and Nonconvex Optimization (Q2945126) (← links)
- How Effectively Train Large-Scale Machine Learning Models? (Q3299229) (← links)
- (Q3385424) (← links)
- Distributed Block Coordinate Descent for Minimizing Partially Separable Functions (Q3462314) (← links)
- (Q4558169) (← links)
- (Q4558495) (← links)
- (Q4558543) (← links)
- Batched Stochastic Gradient Descent with Weighted Sampling (Q4609808) (← links)
- (Q4636973) (← links)
- (Q4637034) (← links)
- On the complexity of parallel coordinate descent (Q4638927) (← links)
- Optimization Methods for Large-Scale Machine Learning (Q4641709) (← links)
- Stochastic Subgradient Estimation Training for Support Vector Machines (Q4922840) (← links)
- (Q4969260) (← links)
- Online training on a budget of support vector machines using twin prototypes (Q4969713) (← links)
- Large‐margin classification with multiple decision rules (Q4970185) (← links)
- Making the Last Iterate of SGD Information Theoretically Optimal (Q4987277) (← links)
- Proximal Gradient Methods for Machine Learning and Imaging (Q5028165) (← links)
- (Q5038378) (← links)
- (Q5096506) (← links)
- (Q5116489) (← links)
- An efficient augmented Lagrangian method for support vector machine (Q5135259) (← links)
- (Q5159437) (← links)
- New nonasymptotic convergence rates of stochastic proximal point algorithm for stochastic convex optimization (Q5162590) (← links)
- New machine-learning algorithms for prediction of Parkinson's disease (Q5172596) (← links)
