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Found 5 papers, 1 papers with code
Efficient Alternating Minimization with Applications to Weighted Low Rank Approximation
For weighted low rank approximation, this improves the runtime of [LLR16] from $n^2 k^2$ to $n^2k$.
Efficient Asynchronize Stochastic Gradient Algorithm with Structured Data
Deep learning has achieved impressive success in a variety of fields because of its good generalization.
A Nearly-Optimal Bound for Fast Regression with $\ell_\infty$ Guarantee
One popular approach for solving such $\ell_2$ regression problem is via sketching: picking a structured random matrix $S\in \mathbb{R}^{m\times n}$ with $m\ll n$ and $SA$ can be quickly computed, solve the ``sketched'' regression problem $\arg\min_{x\in \mathbb{R}^d} \|SAx-Sb\|_2$.
A Data-dependent Approach for High Dimensional (Robust) Wasserstein Alignment
Our framework is a ``data-dependent'' approach that has the complexity depending on the intrinsic dimension of the input data.
On Geometric Alignment in Low Doubling Dimension
In real-world, many problems can be formulated as the alignment between two geometric patterns.
