Name
Title | ||
|---|---|---|
A Dropconnect Deep Computation Model for Highly Heterogeneous Data Feature Learning in Mobile Sensing Networks. |
Abstract | ||
|---|---|---|
Deep computation model, as a tensor deep learning model, outperforms multi-modal deep learning models for feature learning on heterogenous data. However, deep computation model is limited in generalization to small heterogeneous data sets since it typically requires many training objects to learn the parameters. In this article, we propose a dropconnect deep computation model (DDCM) for highly het... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/MNET.2018.1700365 | IEEE Network |
Keywords | Field | DocType |
Computational modeling,Data models,Machine learning,Mobile communication,Training data,Sensors | Kernel (linear algebra),Data modeling,Rectifier (neural networks),Data set,Computer science,Artificial intelligence,Overfitting,Deep learning,Machine learning,Feature learning,Computation,Distributed computing | Journal |
Volume | Issue | ISSN |
32 | 4 | 0890-8044 |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qingchen Zhang | 1 | 372 | 19.17 |
| Laurence T. Yang | 2 | 6870 | 682.61 |
| Zhikui Chen | 3 | 692 | 66.76 |
| Peng Li | 4 | 49 | 2.89 |