- Referenced in 177 articles
- features are: multiple experimenter/laboratory/subjectpool/experiment classes/language support, attribute query selection, random recruitment, public and internal experiment...
- Referenced in 454 articles
- temporal logics PCTL and CSL. The tool features three model checking engines: one symbolic, using ... properties for a range of systems, including randomized distributed algorithms, manufacturing systems and workstation clusters...
- Referenced in 53 articles
- constraint and simple image features, PicHunter is able to locate randomly selected targets...
- Referenced in 32 articles
- experiments. This package provides important features to assure a randomized invitation process based...
- Referenced in 46 articles
- such as feature detectors, feature extractors, (hierarchical) k-means clustering, randomized kd-tree matching...
- Referenced in 20 articles
- select configurations, we focus on speeding up random search through adaptive resource allocation and early ... like iterations, data samples, or features is allocated to randomly sampled configurations. We introduce...
- Referenced in 38 articles
- model with random oracles while maintaining the high-performance feature of CMQV as much...
- Referenced in 154 articles
- copulas. This article presents the design, features, and some implementation details of the R package ... implemented, with methods for density/distribution evaluation, random number generation, and graphical display. Fitting copula-based...
- Referenced in 5 articles
- Learn++.MF: A random subspace approach for the missing feature problem. We introduce Learn ... algorithm that employs random subspace selection to address the missing feature problem in supervised classification ... classifiers, each on a random subset of the available features. Instances with missing values ... effect of the cardinality of the random feature subsets, and the ensemble size on algorithm...
- Referenced in 71 articles
- recent advancements in language modeling and unsupervised feature learning (or deep learning) from sequences ... DeepWalk uses local information obtained from truncated random walks to learn latent representations by treating...
- Referenced in 38 articles
- incremental features. PBS options include: Static/Dynamic decision heuristics, 1-UIP conflict diagnosis, Random restarts...
- Referenced in 83 articles
- nodes to a low-dimensional space of features that maximizes the likelihood of preserving network ... network neighborhood and design a biased random walk procedure, which efficiently explores diverse neighborhoods...
- Referenced in 42 articles
- software is a fast implementation of random forests for high dimensional data. Ensembles of classification ... scale best with the number of features, samples, trees, and features tried for splitting. Finally ... fastest and most memory efficient implementation of random forests to analyze data on the scale...
- Referenced in 45 articles
- identified. Then it is shown what features have been included in the program in order ... allow for the generation of easily reproducible random problem instances. Finally, by applying the generator...
- Referenced in 4 articles
- efficient protocol that employs Thompson sampling, random feature maps, one-rank Cholesky update and automatic...
- Referenced in 6 articles
- generating different initial values. Additional features include random sample generation and contour visualization...
- Referenced in 19 articles
- finds relevant features by comparing original attributes’ importance with importance achievable at random, estimated using...
- Referenced in 99 articles
- Bayesian regression approach which uses dimensionally adaptive random basis elements. Motivated by ensemble methods ... model-free variable selection. BART’s many features are illustrated with a bake-off against...
- Referenced in 22 articles
- that describe complex interactions are a common feature across a number of disciplines, giving rise ... many challenging matrix computational tasks. Several random graph models have been proposed that capture ... solvers. CONTEST (CONtrollable TEST matrices) is a random network toolbox for MATLAB that implements nine ... have one or more parameters that affect features such as sparsity and characteristic pathlength...
- Referenced in 7 articles
- higher order logic. The language features monadic sequencing, recursion, random sampling, failures and failure handling...