kernel hilbert space

Learnware Specification via Label-Aware Neural Embedding AAAI 2025 Nonparametric Teaching for Multiple Learners NeurIPS 2023 A Stein Goodness-of-test for Exponential Random Graph Models AISTATS 2021 Convergences of Regularized Algorithms and Stochastic Gradient Methods with Random Projections JMLR 2020 Unbalanced Sobolev Descent NeurIPS 2020 Consistency of Interpolation with Laplace Kernels is a High-Dimensional Phenomenon COLT 2019 Nonrigid Points Alignment with Soft-weighted Selection IJCAI 2018 Convexified Convolutional Neural Networks ICML 2017 Data sparse nonparametric regression with $ε$-insensitive losses ACML 2017 Group Sparse Additive Machine NeurIPS 2017 ZigZag: A New Approach to Adaptive Online Learning COLT 2017 Context-Aware Gaussian Fields for Non-Rigid Point Set Registration CVPR 2016 Dynamic Mode Decomposition with Reproducing Kernels for Koopman Spectral Analysis NeurIPS 2016 Minimax Estimation of Maximum Mean Discrepancy with Radial Kernels NeurIPS 2016 Regularized Policy Iteration with Nonparametric Function Spaces JMLR 2016 Toward Deeper Understanding of Neural Networks: The Power of Initialization and a Dual View on Expressivity NeurIPS 2016 Excess risk bounds for multitask learning with trace norm regularization COLT 2013 Least Informative Dimensions NeurIPS 2013 q-OCSVM: A q-Quantile Estimator for High-Dimensional Distributions NeurIPS 2013 Spectral Regularization for Support Estimation NeurIPS 2010 Bayesian Network Score Approximation using a Metagraph Kernel NeurIPS 2008 Supervised Bipartite Graph Inference NeurIPS 2008