Discovering Imperfectly Observable Adversarial Actions using Anomaly Detection
Authors: Olga Petrova, Karel Durkota, Galina Alperovich, Karel Horak, Michal Najman, Branislav Bosansky, Viliam Lisy | Published: 2020-04-22
最適化アルゴリズムの選択と評価
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
Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective
Authors: Kaidi Xu, Hongge Chen, Sijia Liu, Pin-Yu Chen, Tsui-Wei Weng, Mingyi Hong, Xue Lin | Published: 2019-06-10 | Updated: 2019-10-14
You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle
Authors: Dinghuai Zhang, Tianyuan Zhang, Yiping Lu, Zhanxing Zhu, Bin Dong | Published: 2019-05-02 | Updated: 2019-11-01
Function Space Particle Optimization for Bayesian Neural Networks
Authors: Ziyu Wang, Tongzheng Ren, Jun Zhu, Bo Zhang | Published: 2019-02-26 | Updated: 2019-05-08
A Frank-Wolfe Framework for Efficient and Effective Adversarial Attacks
Authors: Jinghui Chen, Dongruo Zhou, Jinfeng Yi, Quanquan Gu | Published: 2018-11-27 | Updated: 2019-09-15
Private Selection from Private Candidates
Authors: Jingcheng Liu, Kunal Talwar | Published: 2018-11-19
How to Use Heuristics for Differential Privacy
Authors: Seth Neel, Aaron Roth, Zhiwei Steven Wu | Published: 2018-11-19
Bayesian Compression for Deep Learning
Authors: Christos Louizos, Karen Ullrich, Max Welling | Published: 2017-05-24 | Updated: 2017-11-06
Exponential error rates of SDP for block models: Beyond Grothendieck’s inequality
Authors: Yingjie Fei, Yudong Chen | Published: 2017-05-23