arXiv:1806.06998
Private Text Classification
원문 초록
Confidential text corpora exist in many forms, but do not allow arbitrary sharing. We explore how to use such private corpora using privacy preserving text analytics. We construct typical text processing applications using appropriate privacy preservation techniques (including homomorphic encryption, Rademacher operators and secure computation). We set out the preliminary materials from Rademacher operators for binary classifiers, and then construct basic text processing approaches to match those binary classifiers.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
TokenBreak: Bypassing Text Classification Models Through Token Manipulation
ICS: Total Freedom in Manual Text Classification Supported by Unobtrusive Machine Learning
AdaptText: A Novel Framework for Domain-Independent Automated Sinhala Text Classification
A Method for MBTI Classification Based on Impact of Class Components
A Hybrid Classification Approach using Topic Modeling and Graph Convolution Networks
Targeted Data-driven Regularization for Out-of-Distribution Generalization
토론
이 논문과 연결된 포럼 글이 아직 없습니다.