kernel function

Deep Neural Networks as Gaussian Processes ICLR 2018 Feature-correlation-aware Gaussian Process Latent Variable Model ACML 2018 KELP: a Kernel-based Learning Platform JMLR 2018 Kernelized Synaptic Weight Matrices ICML 2018 Learning Scalable Deep Kernels with Recurrent Structure JMLR 2017 On Quantile Regression in Reproducing Kernel Hilbert Spaces with the Data Sparsity Constraint JMLR 2016 The limits of squared Euclidean distance regularization NeurIPS 2014 A Nonparametric Conjugate Prior Distribution for the Maximizing Argument of a Noisy Function NeurIPS 2012 Breaking the Curse of Kernelization: Budgeted Stochastic Gradient Descent for Large-Scale SVM Training JMLR 2012 Practical Bayesian Optimization of Machine Learning Algorithms NeurIPS 2012 Contextual Gaussian Process Bandit Optimization NeurIPS 2011 Information Rates of Nonparametric Gaussian Process Methods JMLR 2011 Multiple Kernel Learning Algorithms JMLR 2011 Unsupervised Multiple Kernel Learning ACML 2011 Inductive Regularized Learning of Kernel Functions NeurIPS 2010 Learning Translation Invariant Kernels for Classification JMLR 2010 Online Passive-Aggressive Algorithms on a Budget AISTATS 2010 Kernel Methods for Deep Learning NeurIPS 2009 Model Selection for Regression with Continuous Kernel Functions Using the Modulus of Continuity JMLR 2008 A Direct Method for Building Sparse Kernel Learning Algorithms JMLR 2006 Computation of Similarity Measures for Sequential Data using Generalized Suffix Trees NeurIPS 2006 Exact 1-Norm Support Vector Machines Via Unconstrained Convex Differentiable Minimization JMLR 2006 Learning the Kernel Function via Regularization JMLR 2005 Semigroup Kernels on Measures JMLR 2005 On the Influence of the Kernel on the Consistency of Support Vector Machines JMLR 2001