6 citations · 9 across the 23 of their papers we have counts for
4 papers · 2 filters
Optimal Oblivious Subspace Embeddings with Near-optimal Sparsity
Shabarish Chenakkod, Michał Dereziński, Xiaoyu Dong
An oblivious subspace embedding is a random matrix such that, for any -dimensional subspace, with high probability preserves the norms of all vectors in that…
Distributed Least Squares in Small Space via Sketching and Bias Reduction
Sachin Garg, Kevin Tan, Michał Dereziński
Matrix sketching is a powerful tool for reducing the size of large data matrices. Yet there are fundamental limitations to this size reduction when we want to recover an accurate e…
Faster Linear Systems and Matrix Norm Approximation via Multi-level Sketched Preconditioning
Michał Dereziński, Christopher Musco, Jiaming Yang
We present a new class of preconditioned iterative methods for solving linear systems of the form . Our methods are based on constructing a low-rank Nyström approximation t…
Fine-grained Analysis and Faster Algorithms for Iteratively Solving Linear Systems
Michał Dereziński, Daniel LeJeune, Deanna Needell +1
Despite being a key bottleneck in many machine learning tasks, the cost of solving large linear systems has proven challenging to quantify due to problem-dependent quantities such…