Special Issue on Robust Machine Learning

Guest Editors: Daniel Fremont, Mykel Kochenderfer, Alessio Lomuscio, Dragos Margineantu, Cheng Soon-Ong

Journal

Machine Learning

Machine Learning is an international forum focusing on computational approaches to learning.

Daniel Fremont

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Mykel Kochenderfer

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Alessio Lomuscio

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Dragos Margineantu

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Cheng Soon-Ong

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Showing 1-12 of 12 articles

LADDER: Latent boundary-guided adversarial training
Xiaowei Zhou
Ivor W. Tsang
Jie Yin
OriginalPaper Open access 09 September 2022 Pages: 3851 - 3879
Adversarial concept drift detection under poisoning attacks for robust data stream mining
Łukasz Korycki
Bartosz Krawczyk
OriginalPaper 02 June 2022 Pages: 4013 - 4048
Scenic: a language for scenario specification and data generation
Daniel J. Fremont
Edward Kim
Sanjit A. Seshia
OriginalPaper Open access 02 February 2022 Pages: 3805 - 3849
Stronger data poisoning attacks break data sanitization defenses
Pang Wei Koh
Jacob Steinhardt
Percy Liang
OriginalPaper 24 November 2021 Pages: 1 - 47
Guest Editorial: Special issue on robust machine learning
Ransalu Senanayake
Daniel J. Fremont
Cheng Soon Ong
EditorialNotes 09 November 2021 Pages: 2787 - 2789
Global optimization of objective functions represented by ReLU networks
Christopher A. Strong
Haoze Wu
Mykel J. Kochenderfer
OriginalPaper 20 October 2021 Pages: 3685 - 3712
Generating probabilistic safety guarantees for neural network controllers
Sydney M. Katz
Kyle D. Julian
Mykel J. Kochenderfer
OriginalPaper 19 October 2021 Pages: 2903 - 2931
Diametrical Risk Minimization: theory and computations
Matthew D. Norton
Johannes O. Royset
OriginalPaper 02 September 2021 Pages: 2933 - 2951
Byzantine-robust distributed sparse learning for M-estimation
Jiyuan Tu
Weidong Liu
Xiaojun Mao
OriginalPaper 26 July 2021 Pages: 3773 - 3804
Unified SVM algorithm based on LS-DC loss
Shuisheng Zhou
Wendi Zhou
OriginalPaper 21 July 2021 Pages: 2975 - 3002
Metrics and methods for robustness evaluation of neural networks with generative models
Igor Buzhinsky
Arseny Nerinovsky
Stavros Tripakis
OriginalPaper 06 July 2021 Pages: 3977 - 4012
Bayesian optimization with safety constraints: safe and automatic parameter tuning in robotics
Felix Berkenkamp
Andreas Krause
Angela P. Schoellig
OriginalPaper Open access 24 June 2021 Pages: 3713 - 3747

Special Issue on Robust Machine Learning

Participating journal

Machine Learning

Editors

Daniel Fremont

Mykel Kochenderfer

Alessio Lomuscio

Dragos Margineantu

Cheng Soon-Ong

Articles

LADDER: Latent boundary-guided adversarial training

Adversarial concept drift detection under poisoning attacks for robust data stream mining

Scenic: a language for scenario specification and data generation

Stronger data poisoning attacks break data sanitization defenses

Guest Editorial: Special issue on robust machine learning

Global optimization of objective functions represented by ReLU networks

Generating probabilistic safety guarantees for neural network controllers

Diametrical Risk Minimization: theory and computations

Byzantine-robust distributed sparse learning for M-estimation

Unified SVM algorithm based on LS-DC loss

Metrics and methods for robustness evaluation of neural networks with generative models

Bayesian optimization with safety constraints: safe and automatic parameter tuning in robotics

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Special Issue on Robust Machine Learning

Participating journal

Editors

Daniel Fremont

Mykel Kochenderfer

Alessio Lomuscio

Dragos Margineantu

Cheng Soon-Ong

Articles

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