https://deepai.org/publication/low-rank-matrix-approximations-with-flip-flop-spectrum-revealing-qr-factorization
Low-Rank Matrix Approximations with Flip-Flop Spectrum-Revealing QR Factorization | DeepAI
Mar 6, 2018 - 03/06/18 - We present Flip-Flop Spectrum-Revealing QR (Flip-Flop SRQR) factorization, a significantly faster and more reliable variant of the...
rank matrixflip flop
https://arxiv.org/abs/1209.0430
[1209.0430] Fixed-rank matrix factorizations and Riemannian low-rank optimization
Abstract page for arXiv paper 1209.0430: Fixed-rank matrix factorizations and Riemannian low-rank optimization
rank matrix12090430fixedriemannian
https://jmlr.org/papers/v22/20-1067.html
Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent
ill conditionedrank matrixacceleratinglow
https://www.jmlr.org/papers/v22/20-1067.html
Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent
ill conditionedrank matrixacceleratinglow
https://arxiv.org/abs/1103.2816
[1103.2816] Universal low-rank matrix recovery from Pauli measurements
Abstract page for arXiv paper 1103.2816: Universal low-rank matrix recovery from Pauli measurements
rank matrix11032816universallow
https://arxiv.org/abs/2510.05447
[2510.05447] A Probabilistic Basis for Low-Rank Matrix Learning
Abstract page for arXiv paper 2510.05447: A Probabilistic Basis for Low-Rank Matrix Learning
rank matrix251005447probabilisticbasis
https://deepai.org/publication/sampling-based-sublinear-low-rank-matrix-arithmetic-framework-for-dequantizing-quantum-machine-learning
Sampling-based sublinear low-rank matrix arithmetic framework for dequantizing quantum machine...
Oct 14, 2019 - 10/14/19 - We present an algorithmic framework generalizing quantum-inspired polylogarithmic-time algorithms on low-rank matrices. Our work f...
rank matrix
https://openreview.net/forum?id=TG4fKjfvxC
Low-rank Matrix Bandits with Heavy-tailed Rewards | OpenReview
In stochastic low-rank matrix bandit, the expected reward of an arm is equal to the inner product between its feature matrix and some unknown $d_1$ by $d_2$...
rank matrixheavy tailedlowbanditsrewards
https://www.econstor.eu/handle/10419/152479
EconStor: Testing the rank of the Hankel matrix: a statistical approach
EconStor is a publication server for scholarly economic literature, provided as a non-commercial public service by the ZBW.
hankel matrixeconstortestingrankstatistical
https://www.mathworks.com/matlabcentral/answers/401434-rank-of-a-matrix-in-gf
rank of a matrix in gf - MATLAB Answers - MATLAB Central
rank of a matrix in gf. Learn more about matrices, rank
rank of a matrixgfmatlabanswerscentral
https://arxiv.org/abs/1903.02343
[1903.02343] Low-rank updates and divide-and-conquer methods for quadratic matrix equations
Abstract page for arXiv paper 1903.02343: Low-rank updates and divide-and-conquer methods for quadratic matrix equations
https://openreview.net/forum?id=O_FC4kfmV0r
Matrix Estimation for Offline Evaluation in Reinforcement Learning with Low-Rank Structure |...
We consider offline Reinforcement Learning (RL), where the agent does not interact with the environment and must rely on offline data collected using a...
https://jmlr.org/papers/v21/19-359.html
Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely...
https://deepai.org/publication/nonconvex-matrix-factorization-is-geodesically-convex-global-landscape-analysis-for-fixed-rank-matrix-optimization-from-a-riemannian-perspective
Nonconvex Matrix Factorization is Geodesically Convex: Global Landscape Analysis for Fixed-rank...
Sep 29, 2022 - 09/29/22 - We study a general matrix optimization problem with a fixed-rank positive semidefinite (PSD) constraint. We perform the Burer-Mont...
matrix factorizationgeodesically convex
https://www.wolframalpha.com/input/?i=matrix+rank
matrix rank - Wolfram|Alpha
matrix rankwolframalpha
https://arxiv.org/html/2604.04701v1
MUXQ: Mixed-to-Uniform Precision MatriX Quantization via Low-Rank Outlier Decomposition
precision matrix
https://arxiv.org/abs/2403.10547
[2403.10547] Robust Second-Order Nonconvex Optimization and Its Application to Low Rank Matrix...
Abstract page for arXiv paper 2403.10547: Robust Second-Order Nonconvex Optimization and Its Application to Low Rank Matrix Sensing
https://www.nist.gov/publications/combinatorial-rank-attacks-against-rectangular-simple-matrix-encryption-scheme
Combinatorial Rank Attacks Against the Rectangular Simple Matrix Encryption Scheme | NIST
May 12, 2020 - In 2013, Tao et al. introduced the ABC Simple Matrix Scheme for Encryption, a multivariate public key encryption scheme.
matrix encryptioncombinatorialrankattacks
https://www.slideserve.com/tadeo/exploiting-low-rank-structure-in-computing-matrix-powers-with-applications-to-preconditioning
PPT - Exploiting Low-Rank Structure in Computing Matrix Powers with Applications to Preconditioning...
Explore the optimization of algorithms by reorganizing to reduce communication costs in computing matrix powers, focusing on Krylov Subspace Methods....
https://www.econstor.eu/handle/10419/142494
EconStor: Strongly Consistent Determination of the Rank of Matrix
EconStor is a publication server for scholarly economic literature, provided as a non-commercial public service by the ZBW.
strongly consistentof theeconstordeterminationrank
https://www.scirp.org/journal/articles?searchcode=Non-Negative+Matrix+Factorization%3B+Bayesian+Model%3B+Rank+Determination%3B+Probabilistic+Model&searchfield=keyword&page=1
Non-Negative Matrix Factorization; Bayesian Model; Rank Determination; Probabilistic Model -...
Non-Negative Matrix Factorization; Bayesian Model; Rank Determination; Probabilistic Model
non negative matrixbayesian modelfactorizationrankdetermination
https://arxiv.org/abs/2512.01070
[2512.01070] Covariance Estimation for Matrix-variate Data via Fixed-rank Core Covariance Geometry
Abstract page for arXiv paper 2512.01070: Covariance Estimation for Matrix-variate Data via Fixed-rank Core Covariance Geometry
https://arxiv.org/abs/2305.09823
[2305.09823] Parameter optimization for low-rank matrix recovery in hyperspectral imaging
Abstract page for arXiv paper 2305.09823: Parameter optimization for low-rank matrix recovery in hyperspectral imaging
https://www.tensorflow.org/api_docs/python/tf/linalg/matrix_rank?authuser=1
tf.linalg.matrix_rank | TensorFlow v2.16.1
Compute the matrix rank of one or more matrices.
matrix ranktflinalgtensorflowv2
https://arxiv.org/abs/2411.01974
[2411.01974] On the phase diagram of extensive-rank symmetric matrix denoising beyond rotational...
Abstract page for arXiv paper 2411.01974: On the phase diagram of extensive-rank symmetric matrix denoising beyond rotational invariance
https://www.mathworks.com/matlabcentral/answers/818485-find-random-samples-of-some-rows-in-the-matrix-and-ensure-the-rank
Find random samples of some rows in the matrix and ensure the rank - MATLAB Answers - MATLAB Central
Find random samples of some rows in the matrix... Learn more about for loop, while loop, random samples
https://www.unite.ai/lora-qlora-and-qa-lora-efficient-adaptability-in-large-language-models-through-low-rank-matrix-factorization/
LoRa, QLoRA and QA-LoRA: Efficient Adaptability in Large Language Models Through Low-Rank Matrix...
Oct 24, 2023 - Large Language Models (LLMs) have carved a unique niche, offering unparalleled capabilities in understanding and generating human-like text. The power of LLMs...
https://research.google/pubs/the-geometry-of-rank-drop-in-a-class-of-face-splitting-matrix-products/
The Geometry of Rank Drop in a Class of Face-Splitting Matrix Products
the geometrydrop in
https://deepai.org/publication/uncertainty-aware-low-rank-q-matrix-estimation-for-deep-reinforcement-learning
Uncertainty-aware Low-Rank Q-Matrix Estimation for Deep Reinforcement Learning | DeepAI
Nov 19, 2021 - 11/19/21 - Value estimation is one key problem in Reinforcement Learning. Albeit many successes have been achieved by Deep Reinforcement Lear...
deep reinforcement learningq matrix
https://www.unsw.edu.au/science/our-schools/maths/engage-with-us/seminars/2018/low-rank-matrix-recovery-and-completion-maximum-entropy-sampling
Low-rank matrix recovery and completion via maximum entropy sampling | School of Mathematics and...
https://wordnik.com/words/rank%20of%20a%20matrix
rank of a matrix - definition and meaning
rank of a matrixdefinitionmeaning
https://arxiv.org/abs/2604.04701
[2604.04701] MUXQ: Mixed-to-Uniform Precision MatriX Quantization via Low-Rank Outlier Decomposition
Abstract page for arXiv paper 2604.04701: MUXQ: Mixed-to-Uniform Precision MatriX Quantization via Low-Rank Outlier Decomposition