kernel learning

Generalization Properties of hyper-RKHS and its Applications JMLR 2021 Hierarchical Multiple Kernel Clustering AAAI 2021 K-Net: Towards Unified Image Segmentation NeurIPS 2021 Learning Strategies in Decentralized Matching Markets under Uncertain Preferences JMLR 2021 A Convex Parametrization of a New Class of Universal Kernel Functions JMLR 2020 Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels NeurIPS 2020 Deep Kernel Survival Analysis and Subject-Specific Survival Time Prediction Intervals MLHC 2020 Deep learning versus kernel learning: an empirical study of loss landscape geometry and the time evolution of the Neural Tangent Kernel NeurIPS 2020 GP-NAS: Gaussian Process Based Neural Architecture Search CVPR 2020 Learning to Learn Kernels with Variational Random Features ICML 2020 Nonparametric Sequential Prediction While Deep Learning the Kernel AISTATS 2020 Sparse Spectrum Warped Input Measures for Nonstationary Kernel Learning NeurIPS 2020 SupMMD: A Sentence Importance Model for Extractive Summarization using Maximum Mean Discrepancy EMNLP 2020 The Statistical Cost of Robust Kernel Hyperparameter Turning NeurIPS 2020 Variational Adversarial Kernel Learned Imitation Learning AAAI 2020 Why bigger is not always better: on finite and infinite neural networks ICML 2020 Black Box Quantiles for Kernel Learning AISTATS 2019 Entangled Kernels IJCAI 2019 Function-Space Distributions over Kernels NeurIPS 2019 Implicit Kernel Learning AISTATS 2019 Kernel Change-point Detection with Auxiliary Deep Generative Models ICLR 2019 Kernelized Bayesian Softmax for Text Generation NeurIPS 2019 Scalable Semi-Supervised SVM via Triply Stochastic Gradients IJCAI 2019 Differentiable Compositional Kernel Learning for Gaussian Processes ICML 2018 Fast Factorization-free Kernel Learning for Unlabeled Chunk Data Streams IJCAI 2018