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Regression

5,004 papers

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Papers

Variational Relevance Vector Machine for Tabular Data ACML 2010
Hierarchical Gaussian Process Regression ACML 2010
Multi-task Learning for Recommender System ACML 2010
Efficient Multioutput Gaussian Processes through Variational Inducing Kernels AISTATS 2010
Kernel Partial Least Squares is Universally Consistent AISTATS 2010
On the Impact of Kernel Approximation on Learning Accuracy AISTATS 2010
Dirichlet Process Mixtures of Generalized Linear Models AISTATS 2010
Learning Nonlinear Dynamic Models from Non-sequenced Data AISTATS 2010
Nonlinear functional regression: a functional RKHS approach AISTATS 2010
Learning Exponential Families in High-Dimensions: Strong Convexity and Sparsity AISTATS 2010
Fast Active-set-type Algorithms for $l1$-regularized Linear Regression AISTATS 2010
Ultra-high Dimensional Multiple Output Learning With Simultaneous Orthogonal Matching Pursuit: Screening Approach AISTATS 2010
The Feature Selection Path in Kernel Methods AISTATS 2010
The Group Dantzig Selector AISTATS 2010
Descent Methods for Tuning Parameter Refinement AISTATS 2010
Exploiting Covariate Similarity in Sparse Regression via the Pairwise Elastic Net AISTATS 2010
Gaussian processes with monotonicity information AISTATS 2010
A Regularization Approach to Nonlinear Variable Selection AISTATS 2010
Conditional Density Estimation via Least-Squares Density Ratio Estimation AISTATS 2010
Bayesian Generalized Kernel Models AISTATS 2010
Matrix-Variate Dirichlet Process Mixture Models AISTATS 2010
Bundle Methods for Regularized Risk Minimization JMLR 2010
Dimensionality Estimation, Manifold Learning and Function Approximation using Tensor Voting JMLR 2010
On the Rate of Convergence of the Bagged Nearest Neighbor Estimate JMLR 2010
Image Denoising with Kernels Based on Natural Image Relations JMLR 2010