subspace embedding

BOIDS: High-Dimensional Bayesian Optimization via Incumbent-Guided Direction Lines and Subspace Embeddings AAAI 2025 Robust Sparsification via Sensitivity ICML 2025 Optimal bounds for ℓ_p sensitivity sampling via ℓ_2 augmentation ICML 2024 Block Subsampled Randomized Hadamard Transform for Nyström Approximation on Distributed Architectures ICML 2023 Sharper Bounds for ℓ_p Sensitivity Sampling ICML 2023 Sketching Algorithms and Lower Bounds for Ridge Regression ICML 2022 Adversarial Robustness of Streaming Algorithms through Importance Sampling NeurIPS 2021 Exponentially Improved Dimensionality Reduction for l1: Subspace Embeddings and Independence Testing COLT 2021 In-Database Regression in Input Sparsity Time ICML 2021 Subspace Embeddings under Nonlinear Transformations ALT 2021 Near Input Sparsity Time Kernel Embeddings via Adaptive Sampling ICML 2020 Optimal Randomized First-Order Methods for Least-Squares Problems ICML 2020 A Framework for Bayesian Optimization in Embedded Subspaces ICML 2019 Antonym-Synonym Classification Based on New Sub-Space Embeddings AAAI 2019 Sketching for Kronecker Product Regression and P-splines AISTATS 2018 Subspace Embedding and Linear Regression with Orlicz Norm ICML 2018 Improved Distributed Principal Component Analysis NeurIPS 2014 Subspace Embeddings for the Polynomial Kernel NeurIPS 2014 Subspace Embeddings and \ell_p-Regression Using Exponential Random Variables COLT 2013