Labeling Complicated Objects: Multi-View Multi-Instance Multi-Label Learning
Authors: Cam-Tu Nguyen, Xiaoliang Wang, Jing Liu, Zhi-Hua Zhou
AAAI 2014 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We perform experiments on 2 multi-view datasets and 3 single-view datasets. |
| Researcher Affiliation | Academia | Cam-Tu Nguyen1,3, Xiaoliang Wang1, Jing Liu2 and Zhi-Hua Zhou1 1 National Key Laboratory for Novel Software Technology, Nanjing University, 210023, China 2 National Key Laboratory of Pattern Recognition, Institute of Automation Chinese Academy of Sciences, China 3 VNU-University of Engineering and Technology, Hanoi, Vietnam |
| Pseudocode | Yes | Algorithm 1 Generative Process for MIMLmix, Algorithm 2 Training with MIMLmix, Algorithm 3 Testing with MIMLmix |
| Open Source Code | No | The paper does not contain any statement about releasing open-source code, nor does it provide a link to a code repository for the methodology described. |
| Open Datasets | Yes | Citeseerx-10k1 contains scientific papers in two views, i.e, content (v1) and citations (v2). Image CLEF (M uller et al. 2010) contains images with two views: visual (v1) and textual (v2). Here, we use the same subset that has been used in (Nguyen, Zhan, and Zhou 2013).1collected from http://citeseerx.ist.psu.edu/index ... Letter Carroll, MSRC-v2 were collected by (Briggs, Xiaoli, and Raich 2012); and IAPRTC-12 dataset was selected from (Escalante et al. 2010). |
| Dataset Splits | Yes | We conduct 30 times evaluation for Image CLEF, each time we use 1000 examples for training and 1000 examples for testing; 10-fold crossvalidation is conducted for the other datasets. |
| Hardware Specification | Yes | Table 4 shows training times of MIML methods on 3 large datasets on the same computer (CPU of 3.3Gz, 4GB memory). |
| Software Dependencies | No | The paper mentions using 'LIBSVM' and describes parameters like 'RBF kernel with C=23 and γ=.5' but does not specify exact version numbers for any software dependencies. |
| Experiment Setup | Yes | For MIMLmix methods, we set 0 = 0.1, K = 200 as default for both datasets, set = .3, = 5 for Citeseerx-10k; and = 10 and = 0 for Image CLEF. M3LDA is conducted with the same setting as in (Nguyen, Zhan, and Zhou 2013) on Image CLEF; and with K = 200, λ = .5, and the number of sampling iterations of 300 on Citeseerx-10k. |