Results 241 to 250 of about 246,254 (290)

Predicting methane adsorption in coal and shale with white-box and black-box machine learning models. [PDF]

Sci Rep
Sheikhshoaei AH, Hadavimoghaddam F, Abuswer MA, Mohaddespour A, Hemmati-Sarapardeh A, Atashrouz S.   +5 more
europepmc   +1 more source

The strength of Nesterov's accelerated gradient in boosting transferability of stealthy adversarial attacks. [PDF]

PLoS One
Lin C, Long S.
europepmc   +1 more source

Decoding the "black-box": explainable artificial intelligence towards trustworthy advancement in respiratory medicine. [PDF]

Breathe (Sheff)
Marchi G.
europepmc   +1 more source

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Too fast unbiased black-box algorithms

Proceedings of the 13th annual conference on Genetic and evolutionary computation, 2011
Unbiased black-box complexity was recently introduced as a refined complexity model for randomized search heuristics (Lehre and Witt, GECCO 2010). For several problems, this notion avoids the unrealistically low complexity results given by the classical model of Droste, Jansen, and Wegener (Theor. Comput. Sci. 2006).
Benjamin Doerr, Timo Kötzing, Carola Doerr   +2 more
semanticscholar   +3 more sources

Effective Black-Box Testing with Genetic Algorithms

Lecture Notes in Computer Science, 2006
Black-box (functional) test cases are identified from functional requirements of the tested system, which is viewed as a mathematical function mapping its inputs onto its outputs. While the number of possible black-box tests for any non-trivial program is extremely large, the testers can run only a limited number of test cases under their resource ...
Mark Last, Abraham Kandel, Last Mark
exaly   +2 more sources

Black Box Algorithms

Encyclopedia of Cryptography and Security, 2011

semanticscholar   +2 more sources

Demonstration of Generating Explanations for Black-Box Algorithms Using Lewis

Proceedings of the VLDB Endowment, 2021
Explainable artificial intelligence (XAI) aims to reduce the opacity of AI-based decision-making systems, allowing humans to scrutinize and trust them. Unlike prior work that attributes the responsibility for an algorithm’s decisions to its inputs as a ...
Paul Yung-Pou Wang, Sainyam Galhotra, Romila Pradhan, Babak Salimi   +3 more
semanticscholar   +1 more source

Jailbreaking Black Box Large Language Models in Twenty Queries

2025 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), 2023
There is growing interest in ensuring that large language models (LLMs) align with human values. However, the alignment of such models is vulnerable to adversarial jailbreaks, which coax LLMs into overriding their safety guardrails. The identification of
Patrick Chao, Alexander Robey, Edgar Dobriban, Hamed Hassani, George Pappas, Eric Wong   +5 more
semanticscholar   +1 more source