Taisuke Yasuda

According to our database, Taisuke Yasuda authored at least 20 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Nearly Linear Sparsification of ℓ_p Subspace Approximation.

David P. Woodruff, Taisuke Yasuda

CoRR, 2024

Coresets for Multiple ℓ_p Regression.

David P. Woodruff, Taisuke Yasuda

CoRR, 2024

SequentialAttention++ for Block Sparsification: Differentiable Pruning Meets Combinatorial Optimization.

Taisuke Yasuda, Kyriakos Axiotis, Gang Fu, MohammadHossein Bateni, Vahab Mirrokni

CoRR, 2024

Coresets for Multiple ℓp Regression.

David P. Woodruff, Taisuke Yasuda

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Reweighted Solutions for Weighted Low Rank Approximation.

David P. Woodruff, Taisuke Yasuda

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Performance of 𝓁₁ Regularization for Sparse Convex Optimization.

Kyriakos Axiotis, Taisuke Yasuda

CoRR, 2023

New Subset Selection Algorithms for Low Rank Approximation: Offline and Online.

David P. Woodruff, Taisuke Yasuda

Proceedings of the 55th Annual ACM Symposium on Theory of Computing, 2023

Online Lewis Weight Sampling.

David P. Woodruff, Taisuke Yasuda

Proceedings of the 2023 ACM-SIAM Symposium on Discrete Algorithms, 2023

Sketching Algorithms for Sparse Dictionary Learning: PTAS and Turnstile Streaming.

Gregory Dexter, Petros Drineas, David P. Woodruff, Taisuke Yasuda

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Sharper Bounds for ℓ_p Sensitivity Sampling.

David P. Woodruff, Taisuke Yasuda

Proceedings of the International Conference on Machine Learning, 2023

Sequential Attention for Feature Selection.

Taisuke Yasuda, Mohammad Hossein Bateni, Lin Chen, Matthew Fahrbach, Gang Fu, Vahab Mirrokni

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Improved Algorithms for Low Rank Approximation from Sparsity.

David P. Woodruff, Taisuke Yasuda

Proceedings of the 2022 ACM-SIAM Symposium on Discrete Algorithms, 2022

High-Dimensional Geometric Streaming in Polynomial Space.

David P. Woodruff, Taisuke Yasuda

Proceedings of the 63rd IEEE Annual Symposium on Foundations of Computer Science, 2022

Active Linear Regression for ℓp Norms and Beyond.

Cameron Musco, Christopher Musco, David P. Woodruff, Taisuke Yasuda

Proceedings of the 63rd IEEE Annual Symposium on Foundations of Computer Science, 2022

2021

Active Sampling for Linear Regression Beyond the $\ell_2$ Norm.

Cameron Musco, Christopher Musco, David P. Woodruff, Taisuke Yasuda

CoRR, 2021

Exponentially Improved Dimensionality Reduction for 𝓁₁: Subspace Embeddings and Independence Testing.

Yi Li, David P. Woodruff, Taisuke Yasuda

CoRR, 2021

Exponentially Improved Dimensionality Reduction for l1: Subspace Embeddings and Independence Testing.

Yi Li, David P. Woodruff, Taisuke Yasuda

Proceedings of the Conference on Learning Theory, 2021

2020

Graph Spanners in the Message-Passing Model.

Manuel Fernandez, David P. Woodruff, Taisuke Yasuda

Proceedings of the 11th Innovations in Theoretical Computer Science Conference, 2020

2019

Tight Kernel Query Complexity of Kernel Ridge Regression and Kernel $k$-means Clustering.

Taisuke Yasuda, David P. Woodruff, Manuel Fernandez

Proceedings of the 36th International Conference on Machine Learning, 2019

The Query Complexity of Mastermind with l_p Distances.

Manuel Fernandez, David P. Woodruff, Taisuke Yasuda

Proceedings of the Approximation, 2019