Search Results for author: Nadiia Chepurko

Found 4 papers, 0 papers with code

Near-Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time

no code implementations16 Jul 2021 Nadiia Chepurko, Kenneth L. Clarkson, Praneeth Kacham, David P. Woodruff

This question is regarding the logarithmic factors in the sketching dimension of existing oblivious subspace embeddings that achieve constant-factor approximation.

Quantum-Inspired Algorithms from Randomized Numerical Linear Algebra

no code implementations9 Nov 2020 Nadiia Chepurko, Kenneth L. Clarkson, Lior Horesh, Honghao Lin, David P. Woodruff

We create classical (non-quantum) dynamic data structures supporting queries for recommender systems and least-squares regression that are comparable to their quantum analogues.

Recommendation Systems

ARDA: Automatic Relational Data Augmentation for Machine Learning

no code implementations21 Mar 2020 Nadiia Chepurko, Ryan Marcus, Emanuel Zgraggen, Raul Castro Fernandez, Tim Kraska, David Karger

Our system has two distinct components: (1) a framework to search and join data with the input data, based on various attributes of the input, and (2) an efficient feature selection algorithm that prunes out noisy or irrelevant features from the resulting join.

Data Augmentation Feature Selection +1

Robust and Sample Optimal Algorithms for PSD Low-Rank Approximation

no code implementations9 Dec 2019 Ainesh Bakshi, Nadiia Chepurko, David P. Woodruff

Our main result is to resolve this question by obtaining an optimal algorithm that queries $O(nk/\epsilon)$ entries of $A$ and outputs a relative-error low-rank approximation in $O(n(k/\epsilon)^{\omega-1})$ time.

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