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Given its widespread application in machine learning and optimization, the Kronecker product emerges as a pivotal linear algebra operator.
Extensions of lipschitz maps into banach spaces
William B Johnson, Joram Lindenstrauss, and Gideon Schechtman · 1986
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A new algorithm for minimizing convex functions over convex sets
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Faster approximate lossy generalized flow via interior point algorithms
Samuel I Daitch and Daniel A Spielman · 2008
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Daniel A Spielman and Nikhil Srivastava · 2008
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Efficient quantum state tomography
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Fast approximation of matrix coherence and statistical leverage
Petros Drineas, Malik Magdon-Ismail, Michael W Mahoney, and David P Woodruff · 2012
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User-friendly tail bounds for sums of random matrices
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Faster ridge regression via the subsampled randomized hadamard transform
Yichao Lu, Paramveer Dhillon, Dean P Foster, and Lyle Ungar · 2013
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Aleksander Madry · 2013
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Osnap: Faster numerical linear algebra algorithms via sparser subspace embeddings
Jelani Nelson and Huy L Nguyên · 2013
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Compressed matrix multiplication
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Optimal cur matrix decompositions
Christos Boutsidis and David P Woodruff · 2014
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Path finding methods for linear programming: Solving linear programs in o (vrank) iterations and faster algorithms for maximum flow
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Uniform sampling for matrix approximation
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Lp row sampling by lewis weights
Michael B Cohen and Richard Peng · 2015
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A faster cutting plane method and its implications for combinatorial and convex optimization
Yin Tat Lee, Aaron Sidford, and Sam Chiu-wai Wong · 2015
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Low-rank approximation and regression in input sparsity time
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Fast quantum algorithms for least squares regression and statistic leverage scores
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Tensor decomposition for signal processing and machine learning
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Low rank approximation with entrywise l1-norm error
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Quantum sdp-solvers: Better upper and lower bounds
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Solving tall dense linear programs in nearly linear time
Jan van den Brand, Yin Tat Lee, Aaron Sidford, and Zhao Song · 2020
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A faster interior point method for semidefinite programming
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Faster energy maximization for faster maximum flow
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Breaking the n-pass barrier: A streaming algorithm for maximum weight bipartite matching
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Quantum computational advantage using photons
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Quantum algorithms and lower bounds for linear regression with norm constraints
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Sketching for kronecker product regression and p-splines
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An almost-linear time algorithm for uniform random spanning tree generation
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Quantum supremacy using a programmable superconducting processor
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Grand unification of quantum algorithms
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Fast sketching of polynomial kernels of polynomial degree
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Quantum speedup for graph sparsification, cut approximation, and laplacian solving
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Quantum algorithms for sampling log-concave distributions and estimating normalizing constants
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Quantum speedups of optimizing approximately convex functions with applications to logarithmic regret stochastic convex bandits
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Speeding up sparsification using inner product search data structures
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Quantum speedups for linear programming via interior point methods
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Quantum regularized least squares
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João F Doriguello, Alessandro Luongo, and Ewin Tang · 2023
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Quantum speedup of leverage score sampling and its application, 2023
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Quantum tomography using state-preparation unitaries
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Training Multi-Layer Over-Parametrized Neural Network in Subquadratic Time
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