Results 11 to 20 of about 426 (214)
Sensors, 2022 A pivotal topic in agriculture and food monitoring is the assessment of the quality and ripeness of agricultural products by using non-destructive testing techniques. Acoustic testing offers a rapid in situ analysis of the state of the agricultural good,
Dominique Albert-Weiss, Ahmad Osman
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The ASEP and Determinantal Point Processes [PDF]
Communications in Mathematical Physics, 2017 We introduce a family of discrete determinantal point processes related to orthogonal polynomials on the real line, with correlation kernels defined via spectral projections for the associated Jacobi matrices. For classical weights, we show how such ensembles arise as limits of various hypergeometric orthogonal polynomials ensembles. We then prove that
Borodin, Alexei, Olshanski, Grigori
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, 2016 In this survey we review two topics concerning determinantal (or fermion) point processes. First, we provide the construction of diffusion processes on the space of configurations whose invariant measure is the law of a determinantal point process. Second, we present some algorithms to sample from the law of a determinantal point process on a finite ...
Laurent Decreusefond +3 more
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Testing Determinantal Point Processes
CoRR, 2020 Determinantal point processes (DPPs) are popular probabilistic models of diversity. In this paper, we investigate DPPs from a new perspective: property testing of distributions. Given sample access to an unknown distribution $q$ over the subsets of a ground set, we aim to distinguish whether $q$ is a DPP distribution, or $ε$-far from all DPP ...
Khashayar Gatmiry +2 more
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Determinantal Point Process as an alternative to NMS [PDF]
Proceedings of the British Machine Vision Conference 2020, 2020 Published in BMVC ...
Samik Some +2 more
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Kronecker Determinantal Point Processes
CoRR, 2016 Determinantal Point Processes (DPPs) are probabilistic models over all subsets a ground set of $N$ items. They have recently gained prominence in several applications that rely on "diverse" subsets. However, their applicability to large problems is still limited due to the $\mathcal O(N^3)$ complexity of core tasks such as sampling and learning.
Mariet, Zelda Elaine, Sra, Suvrit
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Determinantal Point Processes for Coresets
J. Mach. Learn. Res., 2018 When faced with a data set too large to be processed all at once, an obvious solution is to retain only part of it. In practice this takes a wide variety of different forms, and among them "coresets" are especially appealing. A coreset is a (small) weighted sample of the original data that comes with the following guarantee: a cost function can be ...
Tremblay, Nicolas +2 more
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Large-Margin Determinantal Point Processes [PDF]
CoRR, 2014 15 ...
Wei-Lun Chao +3 more
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Markov Determinantal Point Processes
CoRR, 2012 Appears in Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence (UAI2012)
Raja Hafiz Affandi +2 more
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On simulation of continuous determinantal point processes
Statistics and Computing, 2023 AbstractWe review how to simulate continuous determinantal point processes (DPPs) and improve the current simulation algorithms in several important special cases as well as detail how certain types of conditional simulation can be carried out. Importantly we show how to speed up the simulation of the widely used Fourier based projection DPPs, which ...
Frédéric Lavancier, Ege Rubak
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