kernel methods

GraphQNTK: Quantum Neural Tangent Kernel for Graph Data NeurIPS 2022 High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation NeurIPS 2022 How Good Are Low-Rank Approximations in Gaussian Process Regression? AAAI 2022 Hypergraph Modeling via Spectral Embedding Connection: Hypergraph Cut, Weighted Kernel k-Means, and Heat Kernel AAAI 2022 Importance Weighted Kernel Bayes’ Rule ICML 2022 Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning ICML 2022 Inducer-tuning: Connecting Prefix-tuning and Adapter-tuning EMNLP 2022 Instability and Local Minima in GAN Training with Kernel Discriminators NeurIPS 2022 KernelGPA: A Deformable SLAM Back-end RSS 2022 Kernelized Few-Shot Object Detection With Efficient Integral Aggregation CVPR 2022 Kernelized multi-graph matching ACML 2022 Kernel Memory Networks: A Unifying Framework for Memory Modeling NeurIPS 2022 Kernel Methods for Radial Transformed Compositional Data with Many Zeros ICML 2022 Kernel Multimodal Continuous Attention NeurIPS 2022 Kernel Partial Correlation Coefficient --- a Measure of Conditional Dependence JMLR 2022 KERPLE: Kernelized Relative Positional Embedding for Length Extrapolation NeurIPS 2022 Learning Curves for SGD on Structured Features ICLR 2022 Learning from Few Samples: Transformation-Invariant SVMs with Composition and Locality at Multiple Scales NeurIPS 2022 Learning Representation from Neural Fisher Kernel with Low-rank Approximation ICLR 2022 Learning with convolution and pooling operations in kernel methods NeurIPS 2022 Local Metric Learning for Off-Policy Evaluation in Contextual Bandits with Continuous Actions NeurIPS 2022 Log-Linear-Time Gaussian Processes Using Binary Tree Kernels NeurIPS 2022 Measuring dissimilarity with diffeomorphism invariance ICML 2022 Measuring the robustness of Gaussian processes to kernel choice AISTATS 2022 Naming the Most Anomalous Cluster in Hilbert Space for Structures with Attribute Information AAAI 2022