Results 21 to 30 of about 246,254 (290)
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
openaire +2 more sources
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
doaj +1 more source
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
openaire +1 more source
A Survey of Algorithms for Black-Box Safety Validation [PDF]
Journal of Artificial Intelligence Research, 2020 Autonomous cyber-physical systems (CPS) can improve safety and efficiency for safety-critical applications, but require rigorous testing before deployment.
Anthony Corso +4 more
semanticscholar +1 more source
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
doaj +1 more source
Information, Communication & Society, 2021 Efforts to govern algorithms have centerd the ‘black box problem,’ or the opacity of algorithms resulting from corporate secrecy and technical complexity. In this article, I conceptualize a related and equally fundamental challenge for governance efforts:
Kelley Cotter
semanticscholar +1 more source
Using Black-Box Compression Algorithms for Phase Retrieval [PDF]
IEEE Transactions on Information Theory, 2020 Compressive phase retrieval refers to the problem of recovering a structured $n$-dimensional complex-valued vector from its phase-less under-determined linear measurements. The non-linearity of measurements makes designing theoretically-analyzable efficient phase retrieval algorithms challenging.
Milad Bakhshizadeh +2 more
openaire +2 more sources
Unbox the black-box for the medical explainable AI via multi-modal and multi-centre data fusion: A mini-review, two showcases and beyond [PDF]
Information Fusion, 2021 Explainable Artificial Intelligence (XAI) is an emerging research topic of machine learning aimed at unboxing how AI systems’ black-box choices are made. This research field inspects the measures and models involved in decision-making and seeks solutions
Guang Yang, Qinghao Ye, Jun Xia
semanticscholar +1 more source
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
doaj +2 more sources
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
doaj +1 more source