The computed polynomial remainder is congruent with but a small random multiple of the residue, which can be found by a final strict binary field reduction by the modulus. In addition to a computational unit and operations sequencer, the computing hardware also includes a random or pseudo-random...
We give the first black-box reduction from approximation algorithms to truthful approximation mechanisms for a non-trivial class of multi-parameter problems. Specifically, we prove that every welfare-maximization problem that admits a fully polynomial-time approximation scheme (FPTAS) and can be encoded...
The naive classical algorithm based on direct diagonalization runs in time \({\mathcal{O}}({D}^{3})\), where \(D=\,\text{dim}\,({{\mathcal{H}}}_{s})\) is the Hilbert space dimension. Although it can be improved to \({\mathcal{O}}(D)\) using the kernel polynomial ...
[11] proves that if the adversary is given polynomial computational power, and most (count aggregate) queries are answered with o(n) error, the private data can be determined. Moreover, if the adversary is given exponential computational power, and all queries are answered with o(n) error,...
Before performing the mixed regression analyses, a regression model was tested with Time as a continuous predictor (number of months that passed between the assessments) (and condition as categorical predictors). Here, the nth degree (depending on the number of assessments) polynomial of Time was ...
(2019). Power computations for polynomial change in block randomized designs. Journal of Experimental Education, 87(4), 575–595. Article Google Scholar Li, W., Dong, N., & Maynard, R. (2020). Power analysis for two-level multisite randomized cost-effectiveness trials. Journal of ...
Locally weighted polynomial regression (LOESS) curve fitting was performed to examine the association between achieved LDL-C levels and disease progression. Statistical Analysis All statistical analyses were performed using SAS version 9.4 (SAS Inc). For continuous variables with an approximately normal ...
As sensitivity analyses assessing the impact of baseline differences in patient characteristics, we fitted 2 logistic regression models, crude and adjusted for age (cubic polynomial), early-onset disease, and MGFA classification. The crude odds ratio was 6.07 (95% CI, 1.67-22.1), and significance...
(causal) structure identification5. The goal of structure identification is often to learn the entire causal structure, that is, a directed acyclic graph composed of nodes and edges that connect nodes; however, this is generally a non-deterministic polynomial-time hard problem16,22. To learn the...
Both the problems are formulated in terms of NP-hard non-convex quadratic optimization programs; in order to solve them, we resort to Semidefinite Programming (SDP) relaxation and randomization techniques, providing provable-quality sub-optimal solutions with a polynomial time computational complexity. ...