Search Results for author: Chao Shen

Found 18 papers, 4 papers with code

Property Inference Attacks Against GANs

1 code implementation15 Nov 2021 Junhao Zhou, Yufei Chen, Chao Shen, Yang Zhang

In addition, we show that our attacks can be used to enhance the performance of membership inference against GANs.

Fairness Inference Attack

Black-box Adversarial Attacks on Commercial Speech Platforms with Minimal Information

no code implementations19 Oct 2021 Baolin Zheng, Peipei Jiang, Qian Wang, Qi Li, Chao Shen, Cong Wang, Yunjie Ge, Qingyang Teng, Shenyi Zhang

For commercial cloud speech APIs, we propose Occam, a decision-only black-box adversarial attack, where only final decisions are available to the adversary.

Adversarial Attack Speaker Recognition

Optimal Operation of a Hydrogen-based Building Multi-Energy System Based on Deep Reinforcement Learning

no code implementations22 Sep 2021 Liang Yu, Shuqi Qin, Zhanbo Xu, Xiaohong Guan, Chao Shen, Dong Yue

To overcome the challenge, we reformulate the problem as a Markov game and propose an energy management algorithm to solve it based on multi-agent discrete actor-critic with rules (MADACR).

Parameter Prediction

Teacher Model Fingerprinting Attacks Against Transfer Learning

no code implementations23 Jun 2021 Yufei Chen, Chao Shen, Cong Wang, Yang Zhang

To this end, we propose a teacher model fingerprinting attack to infer the origin of a student model, i. e., the teacher model it transfers from.

Transfer Learning

CARTL: Cooperative Adversarially-Robust Transfer Learning

1 code implementation12 Jun 2021 Dian Chen, Hongxin Hu, Qian Wang, Yinli Li, Cong Wang, Chao Shen, Qi Li

In deep learning, a typical strategy for transfer learning is to freeze the early layers of a pre-trained model and fine-tune the rest of its layers on the target domain.

Adversarial Robustness Transfer Learning

Infer-AVAE: An Attribute Inference Model Based on Adversarial Variational Autoencoder

no code implementations30 Dec 2020 Yadong Zhou, Zhihao Ding, Xiaoming Liu, Chao Shen, Lingling Tong, Xiaohong Guan

While using the trending graph neural networks (GNNs) as encoder has the problem that GNNs aggregate redundant information from neighborhood and generate indistinguishable user representations, which is known as over-smoothing.

A Duet Recommendation Algorithm Based on Jointly Local and Global Representation Learning

no code implementations3 Dec 2020 Xiaoming Liu, Shaocong Wu, Zhaohan Zhang, Zhanwei Zhang, Yu Lan, Chao Shen

Knowledge graph (KG), as the side information, is widely utilized to learn the semantic representations of item/user for recommendation system.

Knowledge Graph Embedding

Optimal Resource Allocation for Delay Minimization in NOMA-MEC Networks

no code implementations11 Sep 2020 Fang Fang, Yanqing Xu, Zhiguo Ding, Chao Shen, Mugen Peng, George K. Karagiannidis

We adopt the partial offloading policy, in which each user can partition its computation task into offloading and locally computing parts.

Edge-computing

A Unified Framework for Analyzing and Detecting Malicious Examples of DNN Models

1 code implementation26 Jun 2020 Kaidi Jin, Tianwei Zhang, Chao Shen, Yufei Chen, Ming Fan, Chenhao Lin, Ting Liu

In this paper, we present a unified framework for detecting malicious examples and protecting the inference results of Deep Learning models.

Adversarial Defense

Multi-Agent Deep Reinforcement Learning for HVAC Control in Commercial Buildings

no code implementations25 Jun 2020 Liang Yu, Yi Sun, Zhanbo Xu, Chao Shen, Dong Yue, Tao Jiang, Xiaohong Guan

In this paper, we intend to minimize the energy cost of an HVAC system in a multi-zone commercial building under dynamic pricing with the consideration of random zone occupancy, thermal comfort, and indoor air quality comfort.

Optimizing Privacy-Preserving Outsourced Convolutional Neural Network Predictions

no code implementations22 Feb 2020 Minghui Li, Sherman S. M. Chow, Shengshan Hu, Yuejing Yan, Chao Shen, Qian Wang

This paper proposes a new scheme for privacy-preserving neural network prediction in the outsourced setting, i. e., the server cannot learn the query, (intermediate) results, and the model.

Shielding Collaborative Learning: Mitigating Poisoning Attacks through Client-Side Detection

no code implementations29 Oct 2019 Lingchen Zhao, Shengshan Hu, Qian Wang, Jianlin Jiang, Chao Shen, Xiangyang Luo, Pengfei Hu

Collaborative learning allows multiple clients to train a joint model without sharing their data with each other.

Adversarial Example Detection by Classification for Deep Speech Recognition

no code implementations22 Oct 2019 Saeid Samizade, Zheng-Hua Tan, Chao Shen, Xiaohong Guan

Machine Learning systems are vulnerable to adversarial attacks and will highly likely produce incorrect outputs under these attacks.

General Classification Keyword Spotting +1

Can a composite heart rate variability biomarker shed new insights about autism spectrum disorder in school-aged children?

1 code implementation24 Aug 2018 Martin G. Frasch, Chao Shen, Hau-Tieng Wu, Alexander Mueller, Emily Neuhaus, Raphael A. Bernier, Dana Kamara, Theodore P. Beauchaine

High-frequency heart rate variability (HRV) has identified parasympathetic nervous system alterations in autism spectrum disorder (ASD).

Quantitative Methods Neurons and Cognition

WristAuthen: A Dynamic Time Wrapping Approach for User Authentication by Hand-Interaction through Wrist-Worn Devices

no code implementations22 Oct 2017 Qi Lyu, Zhifeng Kong, Chao Shen, Tianwei Yue

This paper presents a novel user authentication system through wrist-worn devices by analyzing the interaction behavior with users, which is both accurate and efficient for future usage.

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