kernel methods

Consistent Optimal Transport with Empirical Conditional Measures AISTATS 2024 Convolutional Deep Kernel Machines ICLR 2024 Convolutional Spectral Kernel Learning with Generalization Guarantees (Abstract Reprint) AAAI 2024 Data Distribution Valuation NeurIPS 2024 Dense Associative Memory Through the Lens of Random Features NeurIPS 2024 Detecting Change Intervalswith Isolation Distributional Kernel (Abstract Reprint) IJCAI 2024 Differential Privacy in Scalable General Kernel Learning via K-means Nystr\"om Random Features NeurIPS 2024 Distributed Kernel-Driven Data Clustering JMLR 2024 Efficient Convex Algorithms for Universal Kernel Learning JMLR 2024 Evaluating Transferability in Retrieval Tasks: An Approach Using MMD and Kernel Methods CVPR 2024 Exact, Fast and Expressive Poisson Point Processes via Squared Neural Families AAAI 2024 Expanding Sparse Tuning for Low Memory Usage NeurIPS 2024 Fair Kernel K-Means: from Single Kernel to Multiple Kernel NeurIPS 2024 Faithful and Efficient Explanations for Neural Networks via Neural Tangent Kernel Surrogate Models ICLR 2024 Fast and Adversarial Robust Kernelized SDU Learning AISTATS 2024 Generalization error of spectral algorithms ICLR 2024 Geometric Learning with Positively Decomposable Kernels JMLR 2024 Implicit Regularization Paths of Weighted Neural Representations NeurIPS 2024 Infinite-Dimensional Feature Interaction NeurIPS 2024 Inverse M-Kernels for Linear Universal Approximators of Non-Negative Functions NeurIPS 2024 Kermut: Composite kernel regression for protein variant effects NeurIPS 2024 Kernelised Normalising Flows ICLR 2024 Kernelized Normalizing Constant Estimation: Bridging Bayesian Quadrature and Bayesian Optimization AAAI 2024 Kernel Language Entropy: Fine-grained Uncertainty Quantification for LLMs from Semantic Similarities NeurIPS 2024 Kernel Readout for Graph Neural Networks IJCAI 2024