Hybrid Heterogeneous Transfer Learning through Deep Learning
Authors: Joey Zhou, Sinno Pan, Ivor Tsang, Yan Yan
AAAI 2014 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Extensive experiments on several multilingual sentiment classification tasks verify the effectiveness of our proposed approach compared with some baseline methods. |
| Researcher Affiliation | Academia | Nanyang Technological University, Singapore Institute for Infocomm Research, Singapore University of Technology, Sydney, Australia ]The University of Queensland, Australia |
| Pseudocode | Yes | Algorithm 1 Hybrid Heterogeneous Transfer Learning. |
| Open Source Code | No | The paper does not provide any concrete access information (e.g., repository link, explicit statement of code release) for the source code of the methodology described. |
| Open Datasets | Yes | The cross-language sentiment dataset (Prettenhofer and Stein 2010) comprises of Amazon product reviews of three product categories: books, DVDs and music. |
| Dataset Splits | No | The paper specifies a split into 'train file' and 'test file' for the dataset, but does not explicitly mention a 'validation' split or provide details for one. |
| Hardware Specification | No | No specific hardware details (e.g., CPU/GPU models, memory, or cloud instance types) used for running experiments were provided in the paper. |
| Software Dependencies | No | The paper mentions using 'linear support vector machine (SVM) (Fan et al. 2008)' (referring to LIBLINEAR) and 'm SDA and conduct CCA', but does not provide specific version numbers for any software dependencies. |
| Experiment Setup | Yes | Specifically, we choose λ from {0.01, 0.1, 1, 10, 100} for HHTL, choose corruption probability p from {0.5, 0.6, 0.7, 0.8, 0.9} for m SDA from, and fix the number of layers used in m SDA to be 3. We tune the parameter for CL-KCCA (see (5) in (Vinokourov, Shawe Taylor, and Cristianini 2002)), m SDA-CCA, and the parameter β for He Map (See (1) in (Shi et al. 2010)) from {0.01, 0.1, 1, 10, 100}. |