Efficient algorithms to discover alterations with complementary functional association in cancer by Rebecca Sarto Basso (6728921)

“…We provide analytic evidence of the effectiveness of UNCOVER in finding high-quality solutions and show experimentally that UNCOVER finds sets of alterations significantly associated with functional targets in a variety of scenarios. In particular, we show that our algorithms find sets which are better than the ones obtained by the state-of-the-art method, even when sets are evaluated using the statistical score employed by the latter. …”

Practical rules for summing the series of the Tweedie probability density function with high-precision arithmetic by NELSON L. DIAS (8078003)

“…These implementations need to utilize high-precision arithmetic, and are programmed in the Python programming language. A thorough comparison with existing R functions allows the identification of cases when the latter fail, and provide further guidance to their use.…”

Matlab code of a function used in S2 File. by Hiroko Kato Solvang (5718250)

PyNoetic’s classification module supports a range of popular and widely used ML classification models with just a single line of function call. by Gursimran Singh (575288)

Subjects:

(a-c) Sampling event times with an intensity function . by Gerrit Großmann (9585147)

Equilibrium membrane displacement as a function of active force. by Kai Liu (159026)

Test function information. by Chuang Zhang (2199421)

“…A levy flight strategy further improves the algorithm’s ability to jump out of local minima. …”

Local magnetization and susceptibility as a function of temperature from Metropolis simulations with the global archetype model. by Giulio Ruffini (383994)

Samples from IPPs with a mixture of squared exponential intensity function (<i>p</i> = 2). by M. Hassan Tanveer (9596437)

Test function results. by Ruyi Dong (9038174)

“…Finally, the Cauchy-Gaussian mutation strategy is utilized to prevent the algorithm from falling into local traps. These three steps enable LLSKSO to achieve a dynamic balance between local and global search. …”

Benchmark test functions. by Ruyi Dong (9038174)

“…Finally, the Cauchy-Gaussian mutation strategy is utilized to prevent the algorithm from falling into local traps. These three steps enable LLSKSO to achieve a dynamic balance between local and global search. …”

S1 File - by Yuh-Chin T. Huang (17867207)

“…In this study, we developed a computerized algorithm using the python package (pdfplumber) and validated against clinicians’ interpretation. …”

S1 Dataset - by Yuh-Chin T. Huang (17867207)

“…In this study, we developed a computerized algorithm using the python package (pdfplumber) and validated against clinicians’ interpretation. …”

Network life cycle as a function of the distance of the device from the position of the central node. by Changcheng Li (163757)

Efficient Algorithms for GPU Accelerated Evaluation of the DFT Exchange-Correlation Functional by Ryan Stocks (16867476)

“…Two approaches, both leveraging batched dense linear algebra, are found to outperform the others across a suite of molecular benchmarks. We show that batched formation of the XC matrix from the density matrix yields the best performance for large (>O(103) basis functions), sparse systems such as glycine chains and water clusters. …”

Width of stripes as a function of time. by Pratik Mullick (12851011)

CEC2017 basic functions. by Tengfei Ma (597633)

“…<div><p>To address the limitations of the Zebra Optimization Algorithm (ZOA), including insufficient late-stage optimization search capability, susceptibility to local optima, slow convergence, and inadequate exploration, this paper proposes an enhanced Zebra Optimization Algorithm integrating opposition-based learning and a dynamic elite-pooling strategy (OP-ZOA: Opposition-Based Learning Dynamic Elite-Pooling Zebra Optimization Algorithm). he proposed search algorithm employs a good point set-elite opposition-based learning mechanism to initialize the population, enhancing diversity and facilitating escape from local optima. …”

Comparison of algorithms in two cases. by Yi Tao (178829)

Subjects: “…evolutionary genetic algorithm…”

Flow of the NSGA-II algorithm. by Yi Tao (178829)

Subjects: “…evolutionary genetic algorithm…”

IEEE CEC 2017 benchmark function specifications. by Kankan Tang (21474968)