Asymmetric Valleys: Beyond Sharp and Flat Local Minima
Authors: Haowei He, Gao Huang, Yang Yuan
NeurIPS 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | extensive empirical experiments on both modern deep networks and simple 2 layer networks are conducted to validate our assumptions and analyze the intriguing properties of asymmetric valleys. |
| Researcher Affiliation | Academia | 1Institute for Interdisciplinary Information Sciences, Tsinghua University 2Department of Automation, Tsinghua University 3Beijing National Research Center for Information Science and Technology (BNRist) |
| Pseudocode | No | The paper does not contain any structured pseudocode or algorithm blocks. |
| Open Source Code | Yes | Code available at https://github.com/962086838/code-for-Asymmetric-Valley |
| Open Datasets | Yes | We perform experiments with widely used deep networks, i.e.,Res Net-56, Res Net-110, Res Net-164 [19], VGG-16 [45] and Dense Net-100 [23], on the CIFAR-10, CIFAR-100, SVHN and STL-10 image classification datasets. |
| Dataset Splits | No | The paper mentions using standard datasets like CIFAR-10 and CIFAR-100, but it does not explicitly provide specific percentages, sample counts, or refer to predefined validation splits for reproducibility. |
| Hardware Specification | No | The paper does not provide any specific details about the hardware used for running the experiments (e.g., GPU models, CPU types, or memory). |
| Software Dependencies | No | The paper does not specify any software dependencies with version numbers (e.g., specific libraries, frameworks, or programming language versions). |
| Experiment Setup | No | The paper states, 'Specifically, we run the SWA algorithm (with deceasing learning rate) with popular deep networks...following the configurations in [25].' While this refers to an experimental setup, it defers the specific details to a prior work [25] rather than providing them directly in the paper, which does not meet the criteria for 'Yes'. |