Automatic Gating of Attributes in Deep Structure
Authors: Xiaoming Jin, Tao He, Cheng Wan, Lan Yi, Guiguang Ding, Dou Shen
IJCAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experimental results on a manually-labeled subset of Image Net, a-Yahoo and a-Pascal data set justify the superiority of AG-DBN against several baselines including CNN model and other AG-DBN variants. Specifically, it outperforms the CNN model, VGG19, by significantly reducing the classification error from 26.70% to 13.56% on a-Pascal. |
| Researcher Affiliation | Collaboration | Xiaoming Jin1 , Tao He1 , Cheng Wan2, Lan Yi3, Guiguang Ding1, Dou Shen2 1 School of Software, Tsinghua University, Beijing, China 2 Baidu Corporation, Beijing, China 3 Department of Dev Net, Cisco Systems |
| Pseudocode | Yes | Algorithm 1 Overall Learning Algorithm of AG-DBN ... Algorithm 2 Learning the parameters of l-th RBM with given gate matrix |
| Open Source Code | No | The paper provides a link for a dataset (1https://github.com/Tsinghua-IDE/a-Image Net) but no explicit statement or link to the open-source code for the AG-DBN methodology itself. |
| Open Datasets | Yes | a-Image Net Image Net [Russakovsky et al., 2015] is a widely used image data set. ... 1https://github.com/Tsinghua-IDE/a-Image Net ... a-Yahoo data set is collected by [Farhadi et al., 2009] from the Yahoo image search. ... a-Pascal (this data set is also collected by [Farhadi et al., 2009], and attributes in a-Pascal is the same as a-Yahoo). |
| Dataset Splits | No | Validation data are used to help find the best G in N0 rounds. (The paper mentions validation data but does not provide specific split percentages or counts for reproducibility.) |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., GPU models, CPU types, or memory specifications) used for running the experiments. |
| Software Dependencies | No | The paper does not list any specific software dependencies with version numbers (e.g., Python, TensorFlow, or PyTorch versions). |
| Experiment Setup | Yes | Models all consist of 2 hidden layers of size 500 and 300, and an input layer accepting 50*50 gray scale raw image pixels. ... N0 is set to be 30 ... The batch size s is finally set to 50. ... All experimental results are averaged over 5 independent runs. ... 2 hidden layers are both of size 4096 to make the comparison fare. |