Search Results for author: Yao Yang

Found 8 papers, 1 papers with code

Enhancing the "Immunity" of Mixture-of-Experts Networks for Adversarial Defense

no code implementations29 Feb 2024 Qiao Han, Yong Huang, xinling Guo, Yiteng Zhai, Yu Qin, Yao Yang

Recent studies have revealed the vulnerability of Deep Neural Networks (DNNs) to adversarial examples, which can easily fool DNNs into making incorrect predictions.

Adversarial Defense Adversarial Robustness +1

Fraudulent User Detection Via Behavior Information Aggregation Network (BIAN) On Large-Scale Financial Social Network

no code implementations4 Nov 2022 Hanyi Hu, Long Zhang, Shuan Li, Zhi Liu, Yao Yang, Chongning Na

In financial fraud detection, the modus operandi of criminals can be identified by analyzing user profile and their behaviors such as transaction, loaning etc.

Attribute Fraud Detection +1

Learnable Privacy-Preserving Anonymization for Pedestrian Images

1 code implementation24 Jul 2022 Junwu Zhang, Mang Ye, Yao Yang

We further propose a progressive training strategy to improve the performance, which iteratively upgrades the initial anonymization supervision.

Person Re-Identification Privacy Preserving

A framework for massive scale personalized promotion

no code implementations27 Aug 2021 Yitao Shen, Yue Wang, Xingyu Lu, Feng Qi, Jia Yan, Yixiang Mu, Yao Yang, Yifan Peng, Jinjie Gu

In order to do effective optimization in the second stage, counterfactual prediction and noise-reduction are essential for the first stage.

counterfactual

Resource-Aware Pareto-Optimal Automated Machine Learning Platform

no code implementations30 Oct 2020 Yao Yang, Andrew Nam, Mohamad M. Nasr-Azadani, Teresa Tung

In this study, we introduce a novel platform Resource-Aware AutoML (RA-AutoML) which enables flexible and generalized algorithms to build machine learning models subjected to multiple objectives, as well as resource and hard-ware constraints.

Bayesian Optimization BIG-bench Machine Learning +1

End-to-End Parkinson Disease Diagnosis using Brain MR-Images by 3D-CNN

no code implementations13 Jun 2018 Soheil Esmaeilzadeh, Yao Yang, Ehsan Adeli

In this work, we use a deep learning framework for simultaneous classification and regression of Parkinson disease diagnosis based on MR-Images and personal information (i. e. age, gender).

General Classification regression

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