Results 1 to 10 of about 448,068 (183)
Matrix black box algorithms - a survey [PDF]
Bulletin of the Polish Academy of Sciences: Technical Sciences, 2022 The implementations of matrix multiplication on contemporary, vector-oriented, and multicore-oriented computer hardware are very carefully designed and optimized with respect to their efficiency, due to the essential significance of that operation in ...
Jerzy Respondek
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Improving Clinical Translation of Machine Learning Approaches Through Clinician-Tailored Visual Displays of Black Box Algorithms: Development and Validation [PDF]
JMIR Medical Informatics, 2020 BackgroundDespite the promise of machine learning (ML) to inform individualized medical care, the clinical utility of ML in medicine has been limited by the minimal interpretability and black box nature of these algorithms. ObjectiveThe study
Wongvibulsin, Shannon +2 more
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Users’ trust in black-box machine learning algorithms [PDF]
REGE Revista de GestãoPurpose – This paper aims to investigate whether professional data analysts’ trust of black-box systems is increased by explainability artifacts. Design/methodology/approach – The study was developed in two phases.
Heitor Hoffman Nakashima +2 more
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From black-box complexity to designing new genetic algorithms
Theoretical Computer Science, 2015 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Benjamin Doerr, Carola Doerr
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Comparative Research on Application of Adversarial Samples for End-to-End Speaker Identification [PDF]
Jisuanji gongcheng, 2021 In order to explore the security threats and attack effects of the adversarial samples on the end-to-end speaker identification system, this paper analyzes five white box algorithms(FGSM, JSMA, BIM, C&W, PGD) and two black box algorithms(ZOO, HSJA ...
LIAO Junfan, GU Yijun, ZHANG Peijing, LIAO Qian
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Black-box tests for algorithmic stability
Information and Inference: A Journal of the IMA, 2023 Abstract Algorithmic stability is a concept from learning theory that expresses the degree to which changes to the input data (e.g. removal of a single data point) may affect the outputs of a regression algorithm. Knowing an algorithm’s stability properties is often useful for many downstream applications—for example, stability is known ...
Byol Kim, Rina Foygel Barber
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Embryo Selection by “Black-Box” Artificial Intelligence: The Ethical and Epistemic Considerations
Fertility & Reproduction, 2022 Background: The combination of time-lapse imaging and artificial intelligence (AI) offers novel potential for embryo assessment by allowing a vast quantity of image data to be analysed via machine learning.
Yanhe LIU +6 more
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Proceedings of the 23rd ACM Conference on Economics and Computation, 2022 What should regulators of complex algorithms regulate? We propose a model of oversight over 'black-box' algorithms used in high-stakes applications such as lending, medical testing, or hiring. In our model, a regulator is limited in how much she can learn about a black-box model deployed by an agent with misaligned preferences.
Laura Blattner +2 more
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Inverse-coefficient black-box quantum state preparation
New Journal of Physics, 2022 Black-box quantum state preparation is a fundamental building block for many higher-level quantum algorithms. The basic task of black-box state preparation is to transduce the data encoded as computational basis of quantum state into the amplitude.
Shengbin Wang +10 more
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Unbiased black box search algorithms [PDF]
Proceedings of the 13th annual conference on Genetic and evolutionary computation, 2011 We formalize the concept of an unbiased black box algorithm, which generalises the idea previously introduced by Lehre and Witt. Our formalization of bias relates to the symmetry group of the problem class under consideration, establishing a connection with previous work on No Free Lunch. Our definition is motivated and justified by a series of results,
Jonathan E. Rowe, Michael D. Vose
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