Matrix Completion

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

No benchmark for this task in the archive.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

4 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

1 subtask in the archive's task tree.

Most implemented papers archive 2025-07-28

30 shown of 153 papers with code (796 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Graph Convolutional Matrix Completion
  7 Jun 2017 17 repositories listed
  We consider matrix completion for recommender systems from the point of view of link prediction on graphs.
• Matrix Completion and Low-Rank SVD via Fast Alternating Least Squares
  9 Oct 2014 5 repositories listed Syntology ran 0 of 9 samples · 9 unverified
  The matrix-completion problem has attracted a lot of attention, largely as a result of the celebrated Netflix competition.
• Hybrid Recommender System based on Autoencoders
  24 Jun 2016 4 repositories listed
  A standard model for Recommender Systems is the Matrix Completion setting: given partially known matrix of ratings given by users (rows) to items (columns), infer the unknown ratings.
• GLocal-K: Global and Local Kernels for Recommender Systems
  27 Aug 2021 3 repositories listed
  Then, the pre-trained auto encoder is fine-tuned with the rating matrix, produced by a convolution-based global kernel, which captures the characteristics of each item.
• Inductive Matrix Completion Based on Graph Neural Networks
  26 Apr 2019 3 repositories listed Syntology ran 1 of 2 samples · 1 unverified · 2 pointer-only (licence)
  Under the extreme setting where not any side information is available other than the matrix to complete, can we still learn an inductive matrix completion model?
• Unsupervised Metric Learning in Presence of Missing Data
  19 Jul 2018 3 repositories listed
  Here, we present a new algorithm MR-MISSING that extends these previous algorithms and can be used to compute low dimensional representation on data sets with missing entries.
• Sequence-Aware Recommender Systems
  23 Feb 2018 3 repositories listed
  In this work we review existing works that consider information from such sequentially-ordered user- item interaction logs in the recommendation process.
• An Exact and Robust Conformal Inference Method for Counterfactual and Synthetic Controls
  25 Dec 2017 3 repositories listed
  We introduce new inference procedures for counterfactual and synthetic control methods for policy evaluation.
• Estimating Missing Data in Temporal Data Streams Using Multi-directional Recurrent Neural Networks
  23 Nov 2017 3 repositories listed
  Existing methods address this estimation problem by interpolating within data streams or imputing across data streams (both of which ignore important information) or ignoring the temporal aspect of the data and imposing…
• AIR-Net: Adaptive and Implicit Regularization Neural Network for Matrix Completion
  12 Oct 2021 2 repositories listed
  Theoretically, we show that the adaptive regularization of AIR enhances the implicit regularization and vanishes at the end of training.
• Inductive Matrix Completion Using Graph Autoencoder
  25 Aug 2021 2 repositories listed
  However, without node content (i.
• Escaping Saddle Points in Ill-Conditioned Matrix Completion with a Scalable Second Order Method
  7 Sep 2020 2 repositories listed
  We propose an iterative algorithm for low-rank matrix completion that can be interpreted as both an iteratively reweighted least squares (IRLS) algorithm and a saddle-escaping smoothing Newton method applied to a…
• A regularized deep matrix factorized model of matrix completion for image restoration
  29 Jul 2020 2 repositories listed
  In this work, we propose a Regularized Deep Matrix Factorized (RDMF) model for image restoration, which utilizes the implicit bias of the low rank of deep neural networks and the explicit bias of total variation.
• Compressed sensing of low-rank plus sparse matrices
  18 Jul 2020 2 repositories listed
  This manuscript develops similar guarantees showing that m×n matrices that can be expressed as the sum of a rank-r matrix and a s-sparse matrix can be recovered by computationally tractable methods from…
• Matrix Completion with Quantified Uncertainty through Low Rank Gaussian Copula
  18 Jun 2020 2 repositories listed
  The time required to fit the model scales linearly with the number of rows and the number of columns in the dataset.
• Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent
  18 May 2020 2 repositories listed
  Low-rank matrix estimation is a canonical problem that finds numerous applications in signal processing, machine learning and imaging science.
• Indian Regional Movie Dataset for Recommender Systems
  7 Jan 2018 2 repositories listed
  It consists of movies belonging to 18 different Indian regional languages and metadata of users with varying demographics.
• CayleyNets: Graph Convolutional Neural Networks with Complex Rational Spectral Filters
  22 May 2017 2 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  The rise of graph-structured data such as social networks, regulatory networks, citation graphs, and functional brain networks, in combination with resounding success of deep learning in various applications, has…
• Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks
  22 Apr 2017 2 repositories listed
  Matrix completion models are among the most common formulations of recommender systems.
• Low-Rank Inducing Norms with Optimality Interpretations
  9 Dec 2016 2 repositories listed
  A posteriori guarantees on solving an underlying rank constrained optimization problem with these convex relaxations are provided.
• Collaborative Filtering with Graph Information: Consistency and Scalable Methods
  1 Dec 2015 2 repositories listed
  Low rank matrix completion plays a fundamental role in collaborative filtering applications, the key idea being that the variables lie in a smaller subspace than the ambient space.
• Matrix Completion on Graphs
  7 Aug 2014 2 repositories listed
  Our main goal is thus to find a low-rank solution that is structured by the proximities of rows and columns encoded by graphs.
• Contrastive Matrix Completion with Denoising and Augmented Graph Views for Robust Recommendation
  12 Jun 2025 1 repository listed
  Matrix completion is a widely adopted framework in recommender systems, as predicting the missing entries in the user-item rating matrix enables a comprehensive understanding of user preferences.
• N²: A Unified Python Package and Test Bench for Nearest Neighbor-Based Matrix Completion
  4 Jun 2025 1 repository listed
  Nearest neighbor (NN) methods have re-emerged as competitive tools for matrix completion, offering strong empirical performance and recent theoretical guarantees, including entry-wise error bounds, confidence intervals,…
• Adaptively-weighted Nearest Neighbors for Matrix Completion
  14 May 2025 1 repository listed
  In this technical note, we introduce and analyze AWNN: an adaptively weighted nearest neighbor method for performing matrix completion.
• An extrapolated and provably convergent algorithm for nonlinear matrix decomposition with the ReLU function
  31 Mar 2025 1 repository listed
  Nonlinear matrix decomposition (NMD) with the ReLU function, denoted ReLU-NMD, is the following problem: given a sparse, nonnegative matrix X and a factorization rank r, identify a rank-r matrix Θ such that X≈max(0,Θ).
• Interference-Aware Edge Runtime Prediction with Conformal Matrix Completion
  9 Mar 2025 1 repository listed
  Accurately estimating workload runtime is a longstanding goal in computer systems, and plays a key role in efficient resource provisioning, latency minimization, and various other system management tasks.
• Efficient Over-parameterized Matrix Sensing from Noisy Measurements via Alternating Preconditioned Gradient Descent
  1 Feb 2025 1 repository listed
  Specifically, our main objective is to recover a matrix X_⋆ ∈ℝ^(n₁ ×n₂) with rank r_⋆ from noisy measurements using an over-parameterized factorization LR^⊤, where L ∈ℝ^(n₁ ×r), R ∈ℝ^(n₂ ×r) and min{n₁, n₂} ≥r > r_⋆,…
• Robust Matrix Completion for Discrete Rating-Scale Data
  30 Dec 2024 1 repository listed
  In addition, we investigate the performance of the proposed method and its competitors with discrete rating-scale (rather than continuous) data as well as under various missing data mechanisms and types of corrupted…
• On adaptivity and minimax optimality of two-sided nearest neighbors
  20 Nov 2024 1 repository listed
  Nearest neighbor (NN) algorithms have been extensively used for missing data problems in recommender systems and sequential decision-making systems.

Syntology lines on 3 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.