Abstract | ||
---|---|---|
•A private classification algorithm when labeled data is limited is proposed.•A pool of approximately correct label assignments is constructed based on Transductive Support Vector Machines.•Exponential mechanism is applied for sampling the output label assignment from the generated pool.•Utility analysis is given for the proposed algorithm. |
Year | DOI | Venue |
---|---|---|
2017 | 10.1016/j.knosys.2017.07.006 | Knowledge-Based Systems |
Keywords | Field | DocType |
Unlabeled data,TSVM,Differential privacy,Exponential mechanism | Transduction (machine learning),Data mining,Differential privacy,Computer science,Support vector machine,Empirical risk minimization,Artificial intelligence,Labeled data,Convex optimization,Machine learning | Journal |
Volume | Issue | ISSN |
133 | C | 0950-7051 |
Citations | PageRank | References |
0 | 0.34 | 17 |
Authors | ||
3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Xiaoqian Liu | 1 | 3 | 1.05 |
Li Qian-Mu | 2 | 33 | 14.78 |
Tao Li | 3 | 7216 | 393.45 |