Results 1 to 10 of about 93,390 (118)
Improving Clinical Translation of Machine Learning Approaches Through Clinician-Tailored Visual Displays of Black Box Algorithms: Development and Validation. [PDF]
JMIR Med Inform, 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 S, Wu KC, Zeger SL.
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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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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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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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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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Algorithms, 2022 Universal adversarial attacks, which hinder most deep neural network (DNN) tasks using only a single perturbation called universal adversarial perturbation (UAP), are a realistic security threat to the practical application of a DNN for medical imaging ...
Kazuki Koga, Kazuhiro Takemoto
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Combining white box models, black box machines and human interventions for interpretable decision strategies [PDF]
Judgment and Decision Making, 2022 Granting a short-term loan is a critical decision. A great deal of research has concerned the prediction of credit default, notably through Machine Learning (ML) algorithms.
Gregory Gadzinski, Alessio Castello
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Fast Black-Box Quantum State Preparation [PDF]
Quantum, 2022 Quantum state preparation is an important ingredient for other higher-level quantum algorithms, such as Hamiltonian simulation, or for loading distributions into a quantum device to be used e.g.
Johannes Bausch
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NECSUS, 2023 This article argues that the critical study of algorithms must shift its focus from solving the problem of the ‘black box’ to seeing the structures that surround and pose it as a problematic in the first place.
Leo Hansson Nilson
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Mathematics, 2023 In order to overcome the drawbacks of expensive function evaluation in the practical reliability-based design optimization (RBDO) problem, researchers have proposed the black box-based RBDO method.
Li Lu, Yizhong Wu, Qi Zhang, Ping Qiao
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