Homomorphic Matrix Completion
Authors: Xiao-Yang Liu, Zechu (Steven) Li, Xiaodong Wang
NeurIPS 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Finally, on synthetic data and real-world data, we show that both homomorphic nuclear-norm minimization and alternating minimization algorithms achieve accurate recoveries on cyphertexts, verifying the homomorphism property. |
| Researcher Affiliation | Academia | 1Department of Electrical Engineering, Columbia University, New York, 2Department of Computer Science, Columbia University, New York, |
| Pseudocode | Yes | Algorithm 1 Homomorphic matrix completion at the cloud server Algorithm 2 Homomorphic matrix completion at node j, for j = 1, ..., n2 |
| Open Source Code | No | The paper states in the 'Broader Impact Statement' that code is included, but does not provide a direct link or explicit statement in the main body of the paper for the code related to this specific work. |
| Open Datasets | Yes | The real-world datasets include two benchmark datasets for recommendation systems, namely the Movie Lens10M (Top 400)3 and Netflix (Top 400) datasets. The Movie Lens dataset contains ratings of 400 most rated movies made by approximately 7, 000 users, and the Netflix dataset contains ratings of 400 most rated movies made by approximately 480 thousand users. 3https://movielens.org/ |
| Dataset Splits | No | The paper does not explicitly state training, validation, or test dataset splits. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., GPU/CPU models, memory) used for running its experiments. |
| Software Dependencies | No | The paper does not list specific software dependencies with version numbers. |
| Experiment Setup | Yes | We set k = 10 in Alg. 1 and Alg. 2. For the newly introduced compared algorithm FW, we set the privacy parameter = 2 log(1/δ) and δ = 10 6. For the NN and AM algorithms, the setting is the same in Section 6.2. |