T. Yasuda

activity

20192025

most citedSequential Attention for Feature Selection

2 citations · 7 across the 17 of their papers we have counts for

collaborators

Showing 2021 · cs.DSShow all

2 papers · 2 filters

cs.DS2021

Improved Algorithms for Low Rank Approximation from Sparsity

David P. Woodruff, Taisuke Yasuda

We overcome two major bottlenecks in the study of low rank approximation by assuming the low rank factors themselves are sparse. Specifically, (1) for low rank approximation with s…

cs.DS2021

Exponentially Improved Dimensionality Reduction for $ℓ_{1}$ : Subspace Embeddings and Independence Testing

Yi Li, David P. Woodruff, Taisuke Yasuda

Despite many applications, dimensionality reduction in the $ℓ_{1}$ -norm is much less understood than in the Euclidean norm. We give two new oblivious dimensionality reduction tech…

Improved Algorithms for Low Rank Approximation from Sparsity

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

Exponentially Improved Dimensionality Reduction for $ℓ_{1}$ : Subspace Embeddings and Independence Testing