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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://github.com/xindubawukong222/K-Adaptive-CF

공식 코드

Efficient Model-Based Collaborative Filtering with Fast Adaptive PCA

https://github.com/xuehy/depthInpainting

공식 코드

Depth Image Inpainting: Improving Low Rank Matrix Completion with Low Gradient Regularization

https://github.com/yang-song/GASR

공식 코드

Bayesian Matrix Completion via Adaptive Relaxed Spectral Regularization

https://github.com/yaoyzh/Unlabeled_PCA_NeurIPS2021

공식 코드

Unlabeled Principal Component Analysis and Matrix Completion

https://github.com/yunxiaochen/matrixcompletion_mixeddata

공식 코드

A Generalized Latent Factor Model Approach to Mixed-data Matrix Completion with Entrywise Consistency

https://github.com/yuxuanzhao2295/Matrix-Completion-with-Quantified-Uncertainty-through-Low-Rank-Gaussian-Copula

공식 코드

Matrix Completion with Quantified Uncertainty through Low Rank Gaussian Copula

https://gitlab.com/vuthanho/bssmf.jl

공식 코드

Bounded Simplex-Structured Matrix Factorization: Algorithms, Identifiability and Applications

https://github.com/HarishFulara07/MCGraphs-scRNAseq

Matrix Completion on Graphs

https://github.com/HauLiang/Matrix-Completion-Methods

Guaranteed Rank Minimization via Singular Value Projection

https://github.com/LowRankOpt/LRIPy

Low-Rank Inducing Norms with Optimality Interpretations

https://github.com/MadPr0grammer/CF_Project

Indian Regional Movie Dataset for Recommender Systems

https://github.com/OweysMomenzada/Graph-Neural-Networks-for-effecient-Recommender-Systems

Graph Convolutional Matrix Completion

https://github.com/PreferredAI/cornac

Graph Convolutional Matrix Completion

https://github.com/Recvani/benchmark

Hybrid Recommender System based on Autoencoders

https://github.com/SJD1882/Big-Data-Recommender-Systems

Hybrid Recommender System based on Autoencoders

https://github.com/THweinberger/specAna_matComp

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

https://github.com/UnofficialJuliaMirror/MRMissing.jl-d89fa356-2490-5e87-a4cc-d004309f6659

Unsupervised Metric Learning in Presence of Missing Data

https://github.com/UnofficialJuliaMirrorSnapshots/MRMissing.jl-d89fa356-2490-5e87-a4cc-d004309f6659

Unsupervised Metric Learning in Presence of Missing Data

https://github.com/WenjieDu/PyPOTS

Estimating Missing Data in Temporal Data Streams Using Multi-directional Recurrent Neural Networks

https://github.com/WenjieDu/SAITS

Estimating Missing Data in Temporal Data Streams Using Multi-directional Recurrent Neural Networks

https://github.com/ZhiyuLiu3449/APGD

Efficient Over-parameterized Matrix Sensing from Noisy Measurements via Alternating Preconditioned Gradient Descent

https://github.com/amitboy/SGMC

Spectral Geometric Matrix Completion

https://github.com/anon767/CayleyNet

CayleyNets: Graph Convolutional Neural Networks with Complex Rational Spectral Filters

https://github.com/blueghostyi/id-grec

Graph Convolutional Matrix Completion

https://github.com/boennecd/mdgc

Matrix Completion with Quantified Uncertainty through Low Rank Gaussian Copula

https://github.com/cheonsol-lee/IGMC_CX

Inductive Matrix Completion Based on Graph Neural Networks

https://github.com/deshen24/syntheticNN

Causal Matrix Completion

https://github.com/dhpark22/collranking

Preference Completion: Large-scale Collaborative Ranking from Pairwise Comparisons

https://github.com/dmlc/dgl/tree/master/examples/mxnet/_deprecated/gcmc

Graph Convolutional Matrix Completion

https://github.com/dobriban/diagonally_reduced

Matrix Completion from a Few Entries

https://github.com/edongdongchen/EI

Sensing Theorems for Unsupervised Learning in Linear Inverse Problems

https://github.com/ericschulman/fonts_causal_analysis

An Exact and Robust Conformal Inference Method for Counterfactual and Synthetic Controls

https://github.com/ericschulman/fonts_replication

An Exact and Robust Conformal Inference Method for Counterfactual and Synthetic Controls

https://github.com/fleanend/NeuralRecommender

GLocal-K: Global and Local Kernels for Recommender Systems

https://github.com/fleanend/TorchGlocalK

GLocal-K: Global and Local Kernels for Recommender Systems

https://github.com/gotbutchi/Coderschool-Machine-Learning-Final-Project

Sequence-Aware Recommender Systems

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