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kernel learning

102 papers

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Co-occurring keywords

kernel methods (1097) gaussian process (1200) reproducing kernel hilbert space (334) kernel matrix (73) multiple kernel learning (80) bayesian optimization (624) support vector machine (978) bayesian inference (1907) determinantal point process (140) maximum mean discrepancy (164)

Papers

Entangled Kernels - Beyond Separability JMLR 2021
Learning Strategies in Decentralized Matching Markets under Uncertain Preferences JMLR 2021
A Domain-Shrinking based Bayesian Optimization Algorithm with Order-Optimal Regret Performance NIPS 2021
Hierarchical Multiple Kernel Clustering AAAI 2021
Variational Adversarial Kernel Learned Imitation Learning AAAI 2020
Why bigger is not always better: on finite and infinite neural networks ICML 2020
SupMMD: A Sentence Importance Model for Extractive Summarization using Maximum Mean Discrepancy EMNLP 2020
A Convex Parametrization of a New Class of Universal Kernel Functions JMLR 2020
Learning to Learn Kernels with Variational Random Features ICML 2020
Nonparametric Sequential Prediction While Deep Learning the Kernel AISTATS 2020
The Statistical Cost of Robust Kernel Hyperparameter Turning NIPS 2020
Deep Kernel Survival Analysis and Subject-Specific Survival Time Prediction Intervals MLHC 2020
Sparse Spectrum Warped Input Measures for Nonstationary Kernel Learning NIPS 2020
Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels NIPS 2020
Deep learning versus kernel learning: an empirical study of loss landscape geometry and the time evolution of the Neural Tangent Kernel NIPS 2020
GP-NAS: Gaussian Process Based Neural Architecture Search CVPR 2020
Black Box Quantiles for Kernel Learning AISTATS 2019
Kernelized Bayesian Softmax for Text Generation NIPS 2019
Function-Space Distributions over Kernels NIPS 2019
Scalable Semi-Supervised SVM via Triply Stochastic Gradients IJCAI 2019
Entangled Kernels IJCAI 2019
Implicit Kernel Learning AISTATS 2019
To Understand Deep Learning We Need to Understand Kernel Learning ICML 2018
Differentiable Compositional Kernel Learning for Gaussian Processes ICML 2018
Scaling Gaussian Process Regression with Derivatives NIPS 2018