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From black box to glass box: algorithmic explainability as a strategic decision
Information Economics and Policy, 2023The best-performing algorithms are often the least explainable. In parallel, there is growing concern and evidence that algorithms may autonomously engage in misconduct. Inspired by recent regulatory proposals, we propose a simple model of firm compliance and explainability decisions under the threat of (costly and imperfect) regulatory audits.
Xavier Lambin, Adrien Raizonville
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The Black Box Multigrid Numerical Homogenization Algorithm
Journal of Computational Physics, 1998We propose a numerical approach for the homogenization of the permeability in models of single-phase saturated flow. Our approach is motivated by the observation that multiple length scales are captured automatically by robust multilevel iterative solvers, such as black box multigrid.
Moulton, J. David +2 more
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BlackboxBench: A Comprehensive Benchmark of Black-Box Adversarial Attacks
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023Adversarial examples are well-known tools to evaluate the vulnerability of deep neural networks (DNNs). Although lots of adversarial attack algorithms have been developed, it’s still challenging in the practical scenario that the model’s parameters and ...
Meixi Zheng +4 more
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Benchmarking of Continuous Black Box Optimization Algorithms
Evolutionary Computation, 2012Benchmarking of optimization algorithms is necessary to quantitatively assess the performance of optimizers and to understand their strengths and weaknesses. The Black Box Optimization Benchmarking (BBOB) workshops that took place in 2009, 2010, and 2012 during the Genetic and Evolutionary Computation Conference (GECCO) were set up to benchmark both ...
Anne Auger +2 more
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Conference on Empirical Methods in Natural Language Processing, 2023
Prompt-based learning has been an effective paradigm for large pretrained language models (LLM), enabling few-shot or even zero-shot learning. Black-box prompt search has received growing interest recently for its distinctive properties of gradient-free ...
Han Zhou +3 more
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Prompt-based learning has been an effective paradigm for large pretrained language models (LLM), enabling few-shot or even zero-shot learning. Black-box prompt search has received growing interest recently for its distinctive properties of gradient-free ...
Han Zhou +3 more
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Hardness vs Randomness, Revised: Uniform, Non-Black-Box, and Instance-Wise
IEEE Annual Symposium on Foundations of Computer Science, 2022We propose a new approach to the hardness-to-randomness framework and to the $promise-\mathcal{BPP}\ = promise-\mathcal{P}$ conjecture. Classical results rely on non-uniform hardness assumptions to construct derandomization algorithms that work in the ...
Lijie Chen, R. Tell
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Journal of Petroleum Science and Engineering, 2018
We evaluate the application of eight different global search algorithms to the optimization of oil production from a mature field. Our focus is on algorithms that treat the reservoir simulator as a black box, which is the case for most commercial ...
T. Foroud, A. Baradaran, A. Seifi
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We evaluate the application of eight different global search algorithms to the optimization of oil production from a mature field. Our focus is on algorithms that treat the reservoir simulator as a black box, which is the case for most commercial ...
T. Foroud, A. Baradaran, A. Seifi
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The human black-box: The illusion of understanding human better than algorithmic decision-making.
Journal of experimental psychology. General, 2022As algorithms increasingly replace human decision-makers, concerns have been voiced about the black-box nature of algorithmic decision-making. These concerns raise an apparent paradox.
Andrea Bonezzi, M. Ostinelli, J. Melzner
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An Approximated Gradient Sign Method Using Differential Evolution for Black-Box Adversarial Attack
IEEE Transactions on Evolutionary Computation, 2022Recent studies show that deep neural networks are vulnerable to adversarial attacks in the form of subtle perturbations to the input image, which leads the model to output wrong prediction.
C. Li +4 more
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The ethnographer and the algorithm: beyond the black box
Theory and Society, 2020A common theme in social science studies of algorithms is that they are profoundly opaque and function as “black boxes.” Scholars have developed several methodological approaches in order to address algorithmic opacity. Here I argue that we can explicitly enroll algorithms in ethnographic research, which can shed light on unexpected aspects of ...
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