random feature

How Does the ReLU Activation Affect the Implicit Bias of Gradient Descent on High-dimensional Neural Network Regression? COLT 2026 Robust Predictive Uncertainty and Double Descent in Contaminated Bayesian Random Features UAI 2026 Spectral Valleys and Sharp Failures in Greedy Determinant Maximization COLT 2026 Deep Random Features for Scalable Interpolation of Spatiotemporal Data ICLR 2025 Optimized Random Features for the Neural Tangent Kernel (Student Abstract) AAAI 2025 Random Feature Representation Boosting ICML 2025 The Power of Random Features and the Limits of Distribution-Free Gradient Descent ICML 2025 Variance-Reducing Couplings for Random Features ICLR 2025 Adaptive Random Feature Regularization on Fine-tuning Deep Neural Networks CVPR 2024 Asymptotics of Learning with Deep Structured (Random) Features ICML 2024 Batch normalization is sufficient for universal function approximation in CNNs ICLR 2024 Dense Associative Memory Through the Lens of Random Features NeurIPS 2024 Differential Privacy in Scalable General Kernel Learning via K-means Nystr\"om Random Features NeurIPS 2024 Dimension-free deterministic equivalents and scaling laws for random feature regression NeurIPS 2024 Fast and Adversarial Robust Kernelized SDU Learning AISTATS 2024 General Graph Random Features ICLR 2024 How Spurious Features are Memorized: Precise Analysis for Random and NTK Features ICML 2024 Improved Random Features for Dot Product Kernels JMLR 2024 Learning from higher-order correlations, efficiently: hypothesis tests, random features, and neural networks NeurIPS 2024 Locality Sensitive Sparse Encoding for Learning World Models Online ICLR 2024 Multi-layer random features and the approximation power of neural networks UAI 2024 Multiple Descent in the Multiple Random Feature Model JMLR 2024 On Double Descent in Reinforcement Learning with LSTD and Random Features ICLR 2024 Optimal Kernel Quantile Learning with Random Features ICML 2024 Quasi-Monte Carlo Features for Kernel Approximation ICML 2024