Binary Coding based Label Distribution Learning
Authors: Ke Wang, Xin Geng
IJCAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experiments on five benchmark datasets validate the superiority of BCLDL over several state-of-the-art LDL methods. |
| Researcher Affiliation | Academia | MOE Key Laboratory of Computer Network and Information Integration, School of Computer Science and Engineering, Southeast University, Nanjing 210096, China {k.wang, xgeng}@seu.edu.cn |
| Pseudocode | Yes | Algorithm 1 BC-LDL: Train Algorithm |
| Open Source Code | No | The paper does not contain an explicit statement about releasing source code for the described methodology or a link to a code repository. |
| Open Datasets | Yes | We evaluate the proposed algorithms on five different datasets: s-BU 3DFE (scores-Binghamton University 3D Facial Expression) [Zhou et al., 2015], COPM (Crowd Opinion Prediction on Movies) [Geng and Hou, 2015], Twitter LDL [Yang et al., 2017], Ren-CECps [Quan and Ren, 2010] and MORPH [Ricanek and Tesafaye, 2006]. |
| Dataset Splits | Yes | All the results are averaged over 10-fold cross validation in terms of both accuracy and time cost. |
| Hardware Specification | Yes | All the experiments are carried on a PC with Intel (R) Core (TM) CPU i5-6300@2.30GHz and 12GB RAM. |
| Software Dependencies | No | The paper does not provide specific version numbers for any software dependencies or libraries used in the experiments. |
| Experiment Setup | Yes | On s-BU 3DFE, k in BC-LDL is set to 20 and code length is set to 32 bits. The maximum iteration steps in BFGS-LDL is 300 and IIS-LDL is 100. k for AA-k NN is set to 20. On COPM, k in BC-LDL is 30 and code length is 128 bits. The maximum iteration steps in BFGS-LDL is 100 and IIS-LDL is 20. k in AA-k NN is 10. On Twitter LDL, k in BC-LDL is set to 10 and code length is 256 bits. The maximum iteration steps in BFGS-LDL is 300 and IIS-LDL is 50. k in AA-k NN is 10. On Ren-CECps, k in BC-LDL is 20 and code length is set to 64 bits. The maximum iteration steps in BFGS-LDL is 200 and IIS-LDL is 100. k in AAk NN is set to 20. On MORPH, k in BC-LDL is set to 50 and code length is 256 bits. The maximum iteration steps in BFGS-LDL is 100 and IIS-LDL is 20. k in AA-k NN is set to 10. On the five datasets, the insensitivity parameter ε of LDSVR is set to 0.1 and the number of hidden-layer neurons of CPNN is set to 50. |