文献データベース

MEBN-RM: A Mapping between Multi-Entity Bayesian Network and Relational Model

Authors: Cheol Young Park, Kathryn Blackmond Laskey | Published: 2018-06-06 | Updated: 2018-06-08
リレーショナルデータベース
透かし評価
関数マッピング

Adversarial Attack on Graph Structured Data

Authors: Hanjun Dai, Hui Li, Tian Tian, Xin Huang, Lin Wang, Jun Zhu, Le Song | Published: 2018-06-06
グラフ表現学習
バックドア攻撃
モデルの頑健性保証

Adversarial Regression with Multiple Learners

Authors: Liang Tong, Sixie Yu, Scott Alfeld, Yevgeniy Vorobeychik | Published: 2018-06-06
ポイズニング
損失関数
敵対的学習

Improving the Privacy and Accuracy of ADMM-Based Distributed Algorithms

Authors: Xueru Zhang, Mohammad Mahdi Khalili, Mingyan Liu | Published: 2018-06-06
プライバシー保護手法
モデルの頑健性保証
連合学習

Killing four birds with one Gaussian process: the relation between different test-time attacks

Authors: Kathrin Grosse, Michael T. Smith, Michael Backes | Published: 2018-06-06 | Updated: 2020-11-29
プロンプトリーキング
メンバーシップ推論
透かし評価

Set-based Obfuscation for Strong PUFs against Machine Learning Attacks

Authors: Jiliang Zhang, Chaoqun Shen | Published: 2018-06-06 | Updated: 2019-11-13
サイバーセキュリティ
ユーザー認証システム
透かし評価

Evidential Deep Learning to Quantify Classification Uncertainty

Authors: Murat Sensoy, Lance Kaplan, Melih Kandemir | Published: 2018-06-05 | Updated: 2018-10-31
不確実性の定量化
不確実性評価
深層学習手法

An Explainable Adversarial Robustness Metric for Deep Learning Neural Networks

Authors: Chirag Agarwal, Bo Dong, Dan Schonfeld, Anthony Hoogs | Published: 2018-06-05 | Updated: 2018-06-06
敵対的サンプルの検知
敵対的移転性
透かし評価

PAC-learning in the presence of evasion adversaries

Authors: Daniel Cullina, Arjun Nitin Bhagoji, Prateek Mittal | Published: 2018-06-05 | Updated: 2018-06-06
モデルの頑健性保証
損失関数
敵対的移転性

Mitigation of Policy Manipulation Attacks on Deep Q-Networks with Parameter-Space Noise

Authors: Vahid Behzadan, Arslan Munir | Published: 2018-06-04
モデルの頑健性保証
強化学習
敵対的サンプル