GraphSAC: Detecting anomalies in large-scale graphs
Authors: Vassilis N. Ioannidis, Dimitris Berberidis, Georgios B. Giannakis | Published: 2019-10-21
Performance Evaluation
Learning to Learn by Zeroth-Order Oracle
Authors: Yangjun Ruan, Yuanhao Xiong, Sashank Reddi, Sanjiv Kumar, Cho-Jui Hsieh | Published: 2019-10-21 | Updated: 2020-02-07
Cryptomining Makes Noise: a Machine Learning Approach for Cryptojacking Detection
Authors: Maurantonio Caprolu, Simone Raponi, Gabriele Oligeri, Roberto Di Pietro | Published: 2019-10-21 | Updated: 2020-01-28
Deep k-NN Defense against Clean-label Data Poisoning Attacks
Authors: Neehar Peri, Neal Gupta, W. Ronny Huang, Liam Fowl, Chen Zhu, Soheil Feizi, Tom Goldstein, John P. Dickerson | Published: 2019-09-29 | Updated: 2020-08-13
White-Box Adversarial Defense via Self-Supervised Data Estimation
Authors: Zudi Lin, Hanspeter Pfister, Ziming Zhang | Published: 2019-09-13
Defending Against Adversarial Attacks by Suppressing the Largest Eigenvalue of Fisher Information Matrix
Authors: Chaomin Shen, Yaxin Peng, Guixu Zhang, Jinsong Fan | Published: 2019-09-13
nGraph-HE2: A High-Throughput Framework for Neural Network Inference on Encrypted Data
Authors: Fabian Boemer, Anamaria Costache, Rosario Cammarota, Casimir Wierzynski | Published: 2019-08-12 | Updated: 2019-08-29
A systematic review of fuzzing based on machine learning techniques
Authors: Yan Wang, Peng Jia, Luping Liu, Jiayong Liu | Published: 2019-08-04
Boosting Privately: Privacy-Preserving Federated Extreme Boosting for Mobile Crowdsensing
Authors: Yang Liu, Zhuo Ma, Ximeng Liu, Siqi Ma, Surya Nepal, Robert Deng | Published: 2019-07-24 | Updated: 2020-04-10
ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation
Authors: Yuzhe Yang, Guo Zhang, Dina Katabi, Zhi Xu | Published: 2019-05-28