Generative vs. Discriminative: Rethinking The Meta-Continual Learning
Authors: Mohammadamin Banayeeanzade, Rasoul Mirzaiezadeh, Hosein Hasani, Mahdieh Soleymani
NeurIPS 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | extensive experiments on standard benchmarks demonstrate the effectiveness of the proposed method. |
| Researcher Affiliation | Academia | Mohammadamin Banayeeanzade , Rasoul Mirzaiezadeh , Hosein Hasani , Mahdieh Soleymani Baghshah Department of Computer Engineering Sharif University of Technology m.banayeean@gmail.com, mirzaierasoul75@gmail.com hasanih@ce.sharif.edu, soleymani@sharif.edu |
| Pseudocode | No | The paper describes its methods using prose and mathematical formulations but does not include explicit pseudocode or algorithm blocks. |
| Open Source Code | Yes | The code is publicly available at https://github.com/aminbana/Ge MCL. |
| Open Datasets | Yes | We have performed our experiments on Omniglot [27], Mini-Image Net [51], and CIFAR-100 [25] datasets. |
| Dataset Splits | Yes | We use 763 and 200 classes for meta-train and meta-validation respectively, and others for meta-test. ... Mini-Image Net... is divided into 64, 16, 20 classes for train, validation, and test meta-phases respectively. ... CIFAR-100 dataset... we use 70 and 30 classes for meta-train and meta-test phases respectively. |
| Hardware Specification | No | The paper does not explicitly mention any specific hardware details such as GPU models, CPU models, or memory specifications used for running the experiments. |
| Software Dependencies | No | The paper does not provide specific software dependencies with version numbers (e.g., Python, PyTorch, CUDA versions) used for the experiments. |
| Experiment Setup | Yes | The training is done with a learning rate of 0.001, decaying to half every 0.1 of the training length. ... For this dataset, we used 20-way 10-shot and 20-way 30-shot train and validation episodes respectively with 30 query samples for both. |