random fourier feature

Enhancing Kernel Power K-means: Scalable and Robust Clustering with Random Fourier Features and Possibilistic Method AAAI 2026 Finite-Sample Regret Analysis of Nash Q-Learning with Random-Feature Approximation UAI 2026 Scalable Infinitesimal Generator–Based Koopman Learning for Long-Horizon Prediction L4DC 2026 Fast Summation of Radial Kernels via QMC Slicing ICLR 2025 Highly Efficient Self-Adaptive Reward Shaping for Reinforcement Learning ICLR 2025 Information-Based Exploration via Random Features for Reinforcement Learning ACML 2025 One-Pass Feature Evolvable Learning with Theoretical Guarantees ICML 2025 PAK-UCB Contextual Bandit: An Online Learning Approach to Prompt-Aware Selection of Generative Models and LLMs ICML 2025 Unveiling Differences in Generative Models: A Scalable Differential Clustering Approach CVPR 2025 Gaussian Process Neural Additive Models AAAI 2024 Limited Memory Online Gradient Descent for Kernelized Pairwise Learning with Dynamic Averaging AAAI 2024 Preventing Model Collapse in Gaussian Process Latent Variable Models ICML 2024 Revisiting RIP Guarantees for Sketching Operators on Mixture Models JMLR 2024 Stein Random Feature Regression UAI 2024 Towards a Scalable Reference-Free Evaluation of Generative Models NeurIPS 2024 Classically Approximating Variational Quantum Machine Learning with Random Fourier Features ICLR 2023 Efficient Non-parametric Neural Density Estimation and Its Application to Outlier and Anomaly Detection AAAI 2023 Error Estimation for Random Fourier Features AISTATS 2023 Fast Private Kernel Density Estimation via Locality Sensitive Quantization ICML 2023 GeoCLIP: Clip-Inspired Alignment between Locations and Images for Effective Worldwide Geo-localization NeurIPS 2023 On The Relative Error of Random Fourier Features for Preserving Kernel Distance ICLR 2023 On the Size and Approximation Error of Distilled Datasets NeurIPS 2023 Variance Reduced Online Gradient Descent for Kernelized Pairwise Learning with Limited Memory ACML 2023 A Model-Agnostic Randomized Learning Framework based on Random Hypothesis Subspace Sampling ICML 2022 An Adaptive Kernel Approach to Federated Learning of Heterogeneous Causal Effects NeurIPS 2022