Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in [1].
PCA-based Multi-Task Learning: a Random Matrix Approach
Authors: Malik Tiomoko, Romain Couillet, Frederic Pascal
ICML 2023 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Supporting experiments on synthetic and real data benchmarks show that the proposed method achieves comparable performance with state-of-the-art MTL methods but at a significantly reduced computational cost. |
| Researcher Affiliation | Collaboration | 1Huawei Noah s Ark Lab, Paris, France 2LIG-Lab, Université de Grenoble Alpes, France 3L2S Centrale-Supélec, France. |
| Pseudocode | Yes | Algorithm 1. Proposed multi-class MTL SPCA algorithm. |
| Open Source Code | Yes | The proofs and Matlab codes to reproduce our main results and simulations, along with theoretical extensions and additional supporting results, are provided in the supplementary material. |
| Open Datasets | Yes | We here compare the performance of Algorithm 1 (MTL SPCA), on both synthetic and real data benchmarks... Image Clef dataset (Ionescu et al., 2017) ... Amazon review (textual) dataset8 (Blitzer et al., 2007) and the MNIST (image) dataset (Deng, 2012). |
| Dataset Splits | Yes | Figure 2. (Left) Theoretical (Th)/empirical (Emp) error rate for 2-class Gaussian mixture transfer with means µ1 = e[p] 1 , µ 1 = e[p] p , µ2 = βµ1 + p 1 β2µ 1 , p = 100, n1j = 1 000, n2j = 50; (Right) running time comparison (in sec); n = 2p, ntj/n = 0.25. |
| Hardware Specification | No | The paper mentions experiments were run 'on a modern laptop' but does not provide specific hardware details such as CPU or GPU models, or memory specifications. |
| Software Dependencies | No | The paper mentions 'Matlab codes' and 'Mex files' but does not provide specific version numbers for Matlab or any other software dependencies. |
| Experiment Setup | Yes | Figure 2. (Left) Theoretical (Th)/empirical (Emp) error rate for 2-class Gaussian mixture transfer with means µ1 = e[p] 1 , µ 1 = e[p] p , µ2 = βµ1 + p 1 β2µ 1 , p = 100, n1j = 1 000, n2j = 50; (Right) running time comparison (in sec); n = 2p, ntj/n = 0.25. |