The Query Complexity of Mastermind with lp Distances. - Manuel Fernandez; David P. Woodruff; Taisuke Yasuda 002 (APPROX-RANDOM, 2019)

Tight Kernel Query Complexity of Kernel Ridge Regression and Kernel $k$-means Clustering. - Taisuke Yasuda 002; David P. Woodruff; Manuel Fernandez (ICML, 2019)

Graph Spanners in the Message-Passing Model. - Manuel Fernandez; David P. Woodruff; Taisuke Yasuda 002 (ITCS, 2020)

Exponentially Improved Dimensionality Reduction for l1: Subspace Embeddings and Independence Testing. - Yi Li 002; David P. Woodruff; Taisuke Yasuda 002 (COLT, 2021)

Exponentially Improved Dimensionality Reduction for 𝓁1: Subspace Embeddings and Independence Testing. - Yi Li 002; David P. Woodruff; Taisuke Yasuda 002 (CoRR, 2021)

Active Sampling for Linear Regression Beyond the $ ell_2$ Norm. - Cameron Musco; Christopher Musco; David P. Woodruff; Taisuke Yasuda 002 (CoRR, 2021)

Active Linear Regression for ℓp Norms and Beyond. - Cameron Musco; Christopher Musco; David P. Woodruff; Taisuke Yasuda 002 (FOCS, 2022)

High-Dimensional Geometric Streaming in Polynomial Space. - David P. Woodruff; Taisuke Yasuda 002 (FOCS, 2022)

Improved Algorithms for Low Rank Approximation from Sparsity. - David P. Woodruff; Taisuke Yasuda 002 (SODA, 2022)

Sequential Attention for Feature Selection. - Taisuke Yasuda 002; Mohammad Hossein Bateni 001; Lin Chen; Matthew Fahrbach; Gang Fu; Vahab Mirrokni (ICLR, 2023)

Sharper Bounds for ℓp Sensitivity Sampling. - David P. Woodruff; Taisuke Yasuda 002 (ICML, 2023)

Sketching Algorithms for Sparse Dictionary Learning: PTAS and Turnstile Streaming. - Gregory Dexter; Petros Drineas; David P. Woodruff; Taisuke Yasuda 002 (NeurIPS, 2023)

Online Lewis Weight Sampling. - David P. Woodruff; Taisuke Yasuda 002 (SODA, 2023)

New Subset Selection Algorithms for Low Rank Approximation: Offline and Online. - David P. Woodruff; Taisuke Yasuda 002 (STOC, 2023)

Performance of 𝓁1 Regularization for Sparse Convex Optimization. - Kyriakos Axiotis; Taisuke Yasuda 002 (CoRR, 2023)

Reweighted Solutions for Weighted Low Rank Approximation. - David P. Woodruff; Taisuke Yasuda 002 (ICML, 2024)

Coresets for Multiple ℓp Regression. - David P. Woodruff; Taisuke Yasuda 002 (ICML, 2024)

SequentialAttention++ for Block Sparsification: Differentiable Pruning Meets Combinatorial Optimization. - Taisuke Yasuda 002; Kyriakos Axiotis; Gang Fu; Mohammad Hossein Bateni 001; Vahab Mirrokni (NeurIPS, 2024)

John Ellipsoids via Lazy Updates. - David P. Woodruff; Taisuke Yasuda 002 (NeurIPS, 2024)

Coresets for Multiple ℓp Regression. - David P. Woodruff; Taisuke Yasuda 002 (CoRR, 2024)

Nearly Linear Sparsification of ℓp Subspace Approximation. - David P. Woodruff; Taisuke Yasuda 002 (CoRR, 2024)

Algorithms for Matrix Approximation: Sketching, Sampling, and Sparse Optimization - Taisuke Yasuda 002 (2024)

Streaming Algorithms For ℓp Flows and ℓp Regression. - Amit Chakrabarti; Jeffrey Jiang; David P. Woodruff; Taisuke Yasuda 002 (ICLR, 2025)