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Matrix Completion

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Matrix Completion is a method for recovering lost information. It originates from machine learning and usually deals with highly sparse matrices. Missing or unknown data is estimated using the low-rank matrix of the known data.

Source: A Fast Matrix-Completion-Based Approach for Recommendation Systems

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://bitbucket.org/cdal/dcmf

공식 코드

Deep Collective Matrix Factorization for Augmented Multi-View Learning

https://gitee.com/lizhemin15/rmnn-pip

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A regularized deep matrix factorized model of matrix completion for image restoration

https://github.com/AudeSportisse/stat

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Imputation and low-rank estimation with Missing Not At Random data

https://github.com/FWen/ncreg

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A Survey on Nonconvex Regularization Based Sparse and Low-Rank Recovery in Signal Processing, Statistics, and Machine Learning

https://github.com/FWen/nmc

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Matrix Completion via Nonconvex Regularization: Convergence of the Proximal Gradient Algorithm

https://github.com/HazyResearch/metal

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Training Complex Models with Multi-Task Weak Supervision

https://github.com/HuyanHuang/tensor-completion-via-tensor-ring-decomposition

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Provable Tensor Ring Completion

https://github.com/Jinshengg/SHGD

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Projected Gradient Descent for Spectral Compressed Sensing via Symmetric Hankel Factorization

https://github.com/LowRankOpt/LRINorm

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Low-Rank Inducing Norms with Optimality Interpretations

https://github.com/NicholasJohnson2020/LearningLowRankMatrices

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Predictive Low Rank Matrix Learning under Partial Observations: Mixed-Projection ADMM

https://github.com/Not-IITian/functional-matrix-completion

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Geometric Matrix Completion: A Functional View

https://github.com/Stef-hub/partial_trace_kraus

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Partial Trace Regression and Low-Rank Kraus Decomposition

https://github.com/Titan-Tong/ScaledGD

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Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent

https://github.com/XuFengthucs/fSVT

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Faster Matrix Completion Using Randomized SVD

https://github.com/ZAL-NASK/CSMC

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Randomized Approach to Matrix Completion: Applications in Collaborative Filtering and Image Inpainting

https://github.com/aalfons/rdmc

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Robust Matrix Completion for Discrete Rating-Scale Data

https://github.com/aanchalMongia/DeepVir

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DeepVir -- Graphical Deep Matrix Factorization for "In Silico" Antiviral Repositioning: Application to COVID-19

https://github.com/aashish-khub/NearestNeighbors

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N$^2$: A Unified Python Package and Test Bench for Nearest Neighbor-Based Matrix Completion

https://github.com/amoliu/CayleyNet

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CayleyNets: Graph Convolutional Neural Networks with Complex Rational Spectral Filters

https://github.com/andrewssobral/lrslibrary

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Decomposition into Low-rank plus Additive Matrices for Background/Foreground Separation: A Review for a Comparative Evaluation with a Large-Scale Dataset

https://github.com/anikpram/Deep-SLR

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Deep Generalization of Structured Low-Rank Algorithms (Deep-SLR)

https://github.com/aradha/lin-rfm

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Linear Recursive Feature Machines provably recover low-rank matrices

https://github.com/arashmahyari/PolicyAugmentation

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Policy Augmentation: An Exploration Strategy for Faster Convergence of Deep Reinforcement Learning Algorithms

https://github.com/arthurmensch/modl

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Dictionary Learning for Massive Matrix Factorization

https://github.com/bestadcarry/mi-nngp

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Multiple Imputation with Neural Network Gaussian Process for High-dimensional Incomplete Data

https://github.com/caiting123321/AT_NMF

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Adversarially-Trained Nonnegative Matrix Factorization

https://github.com/cbig-iowa/giraf

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Structured Low-Rank Algorithms: Theory, MR Applications, and Links to Machine Learning

https://github.com/cchao0116/GSIMC-ICLR2023

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Graph Signal Sampling for Inductive One-Bit Matrix Completion: a Closed-form Solution

https://github.com/chaoshangcs/VIGAN

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VIGAN: Missing View Imputation with Generative Adversarial Networks

https://github.com/cjyaras/deep-lora-transformers

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Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation

https://github.com/ckuemmerle/MatrixIRLS

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Escaping Saddle Points in Ill-Conditioned Matrix Completion with a Scalable Second Order Method

https://github.com/crabtain959/synbeats

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Forecasting Algorithms for Causal Inference with Panel Data

https://github.com/diliadis/deepmtp

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Hyperparameter optimization in deep multi-target prediction

https://github.com/drormoran/Equivariant-SFM

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Deep Permutation Equivariant Structure from Motion

https://github.com/e-bug/unit-mf

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Matrix Completion in the Unit Hypercube via Structured Matrix Factorization

https://github.com/ejmric/trifaststmf

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Matrix tri-factorization over the tropical semiring

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