SMAP: A Joint Dimensionality Reduction Scheme for Secure Multi-Party
Visualization

SMAP: A Joint Dimensionality Reduction Scheme for Secure Multi-Party Visualization

30 July 2020

Lei Zhang

Yang Chen

Papers citing "SMAP: A Joint Dimensionality Reduction Scheme for Secure Multi-Party Visualization"

10 / 10 papers shown

Title
A Survey of Visual Analytics Techniques for Machine Learning Jun Yuan Changjian Chen Weikai Yang Mengchen Liu Jiazhi Xia Shixia Liu 64 221 0 21 Aug 2020
OoDAnalyzer: Interactive Analysis of Out-of-Distribution Samples Changjian Chen Jun Yuan Yafeng Lu Yang Liu Hang Su Songtao Yuan Shixia Liu OODD 40 64 0 08 Feb 2020
AutoGAN-based Dimension Reduction for Privacy Preservation Hung Nguyen Di Zhuang Pei-Yuan Wu Jerome Chang 33 33 0 27 Feb 2019
Federated Machine Learning: Concept and Applications Qiang Yang Yang Liu Tianjian Chen Yongxin Tong FedML 59 2,302 0 13 Feb 2019
Visual Designs for Binned Aggregation of Multi-Class Scatterplots Florian Heimerl Chih-Ching Chang Alper Sarıkaya Michael Gleicher 26 18 0 04 Oct 2018
Federated Learning with Non-IID Data Yue Zhao Meng Li Liangzhen Lai Naveen Suda Damon Civin Vikas Chandra FedML 139 2,547 0 02 Jun 2018
Model-based Pricing for Machine Learning in a Data Marketplace Lingjiao Chen Paraschos Koutris Arun Kumar 34 123 0 26 May 2018
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction Leland McInnes John Healy James Melville 146 9,312 0 09 Feb 2018
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 175 6,069 0 01 Jul 2016
Efficient Private Statistics with Succinct Sketches Luca Melis G. Danezis Emiliano De Cristofaro 34 124 0 25 Aug 2015