Multi-kernel regularized classifiers
Journal of Complexity
Learnability of Gaussians with Flexible Variances
The Journal of Machine Learning Research
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part I
A numerical algorithm for zero counting, I: Complexity and accuracy
Journal of Complexity
Learning from uniformly ergodic Markov chains
Journal of Complexity
Error bounds of multi-graph regularized semi-supervised classification
Information Sciences: an International Journal
Hermite learning with gradient data
Journal of Computational and Applied Mathematics
Semisupervised multicategory classification with imperfect model
IEEE Transactions on Neural Networks
Moving least-square method in learning theory
Journal of Approximation Theory
Classification with Gaussians and Convex Loss
The Journal of Machine Learning Research
Bounded Kernel-Based Online Learning
The Journal of Machine Learning Research
Learning Translation Invariant Kernels for Classification
The Journal of Machine Learning Research
Rademacher chaos complexities for learning the kernel problem
Neural Computation
Learning gradients via an early stopping gradient descent method
Journal of Approximation Theory
Logistic classification with varying Gaussians
Computers & Mathematics with Applications
A new scheme to learn a kernel in regularization networks
Neurocomputing
Full length article: Concentration estimates for the moving least-square method in learning theory
Journal of Approximation Theory
The consistency analysis of coefficient regularized classification with convex loss
WSEAS Transactions on Mathematics
Generalization bounds of ERM algorithm with V-geometrically Ergodic Markov chains
Advances in Computational Mathematics
MMCS'08 Proceedings of the 7th international conference on Mathematical Methods for Curves and Surfaces
Refinement of operator-valued reproducing kernels
The Journal of Machine Learning Research
Bound the learning rates with generalized gradients
WSEAS Transactions on Signal Processing
Classification with non-i.i.d. sampling
Mathematical and Computer Modelling: An International Journal
Learning Rates for Regularized Classifiers Using Trigonometric Polynomial Kernels
Neural Processing Letters
On Dimension-independent Rates of Convergence for Function Approximation with Gaussian Kernels
SIAM Journal on Numerical Analysis
Geometry of online packing linear programs
ICALP'12 Proceedings of the 39th international colloquium conference on Automata, Languages, and Programming - Volume Part I
Full length article: Support vector machines regression with l1-regularizer
Journal of Approximation Theory
An approximation theory approach to learning with l1 regularization
Journal of Approximation Theory
Sampling scattered data with Bernstein polynomials: stochastic and deterministic error estimates
Advances in Computational Mathematics
Approximation and estimation bounds for free knot splines
Computers & Mathematics with Applications
Learning with boundary conditions
Neural Computation
Conditional quantiles with varying Gaussians
Advances in Computational Mathematics
Learning theory approach to minimum error entropy criterion
The Journal of Machine Learning Research
Learning with coefficient-based regularization and ℓ1-penalty
Advances in Computational Mathematics
Approximation and Estimation Bounds for Subsets of Reproducing Kernel Kreĭn Spaces
Neural Processing Letters
Generalization Bounds of Regularization Algorithm with Gaussian Kernels
Neural Processing Letters
Detecting network communities using regularized spectral clustering algorithm
Artificial Intelligence Review
Statistical analysis of the moving least-squares method with unbounded sampling
Information Sciences: an International Journal
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