Self-training For Few-shot Transfer Across Extreme Task Differences
Authors: Cheng Perng Phoo, Bharath Hariharan
ICLR 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | 5 EXPERIMENTS, 5.1 FEW-SHOT TRANSFER ACROSS DRASTICALLY DIFFERENT DOMAINS, 5.1.1 RESULTS |
| Researcher Affiliation | Academia | Cheng Perng Phoo, Bharath Hariharan Department of Computer Science Cornell University {cpphoo, bharathh}@cs.cornell.edu |
| Pseudocode | No | The paper describes its method using prose and equations, but does not include any explicitly labeled pseudocode or algorithm blocks. |
| Open Source Code | Yes | Our code is available at https://github.com/cpphoo/STARTUP. |
| Open Datasets | Yes | We experiment with the challenging (BSCD-FSL) benchmark introduced in Guo et al. (2020). The base dataset in this benchmark is mini Image Net (Vinyals et al., 2016)... Crop Diseases, Euro SAT, ISIC2018, Chest X |
| Dataset Splits | Yes | To pick the suitable starting learning rate, 10% of the unlabeled data and 5% of the labeled data (1% when using Image Net as the base dataset) are set aside as our internal validation set. |
| Hardware Specification | No | The paper does not provide specific hardware details such as GPU models, CPU types, or cloud computing specifications used for running experiments. |
| Software Dependencies | No | The paper mentions PyTorch and scikit-learn with citations, but does not explicitly state specific version numbers for these software dependencies (e.g., "PyTorch 1.9"). |
| Experiment Setup | Yes | The student model is trained for 1000 epochs... We use a batch size of 256... We use the SGD with momentum optimizer with momentum 0.9 and weight decay 1e-4. To pick the suitable starting learning rate, 10% of the unlabeled data and 5% of the labeled data... are set aside as our internal validation set. We pick the starting learning rate by training the student with starting learning rate lr {1e-1, 5e-2, 3e-2, 1e-2, 5e-3, 3e-3, 1e-3}... |