共 50 条
[41]
Revisiting Black-box Ownership Verification for Graph Neural Networks
[J].
45TH IEEE SYMPOSIUM ON SECURITY AND PRIVACY, SP 2024,
2024,
:2478-2496
[42]
Feature Importance Explanations for Temporal Black-Box Models
[J].
THIRTY-SIXTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTY-FOURTH CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE / TWELVETH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE,
2022,
:8351-8360
[43]
Uncertainty propagation method for high-dimensional black-box problems via Bayesian deep neural network
[J].
Structural and Multidisciplinary Optimization,
2022, 65
[44]
Comparing Explanations from Glass-Box and Black-Box Machine-Learning Models
[J].
COMPUTATIONAL SCIENCE - ICCS 2022, PT III,
2022, 13352
:668-675
[46]
Local Explanations and Self-Explanations for Assessing Faithfulness in black-box LLMs
[J].
PROCEEDINGS OF THE 13TH HELLENIC CONFERENCE ON ARTIFICIAL INTELLIGENCE, SETN 2024,
2024,
[47]
Compressing Deep Neural Network: A Black-Box System Identification Approach
[J].
2021 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN),
2021,
[48]
AdverseGen: A Practical Tool for Generating Adversarial Examples to Deep Neural Networks Using Black-Box Approaches
[J].
ARTIFICIAL INTELLIGENCE XXXVIII,
2021, 13101
:313-326
[49]
A Black-Box Attack on Neural Networks Based on Swarm Evolutionary Algorithm
[J].
INFORMATION SECURITY AND PRIVACY, ACISP 2020,
2020, 12248
:268-284
[50]
SOTER: Guarding Black-box Inference for General Neural Networks at the Edge
[J].
PROCEEDINGS OF THE 2022 USENIX ANNUAL TECHNICAL CONFERENCE,
2022,
:723-737