- Referenced in 594 articles
- sparse matrix algorithms. It allows for robust and repeatable experiments: robust because performance results with...
- Referenced in 591 articles
- rotation, and are shown to provide robust matching across a substantial range of affine distortion ... pose parameters. This approach to recognition can robustly identify objects among clutter and occlusion while...
- Referenced in 534 articles
- velocities at the interface. The stability and robustness of the HLLE solver is closely related ... middle wave speed. They are quite robust and efficient but somewhat more diffusive...
- Referenced in 375 articles
- package robustbase: Basic Robust Statistics. ”Essential” Robust Statistics. The goal is to provide tools allowing ... analyze data with robust methods. This includes regression methodology including model selections and multivariate statistics ... where we strive to cover the book ”Robust Statistics, Theory and Methods” by Maronna, Martin...
- Referenced in 357 articles
- element code. The programming environment provides a robust tool for extended finite element (XFEM) computations ... natural requirements for modularity, extensibility, and robustness. To facilitate mesh -- geometry interactions with hundreds...
- Referenced in 265 articles
- international reputation as a source of robust and efficient numerical software. Among its best known...
- Referenced in 258 articles
- PARDISO is a thread-safe, high-performance, robust, memory efficient and easy to use software...
- Referenced in 159 articles
- SURF: Speeded Up Robust Features. In this paper, we present a novel scale- and rotation ... detector and descriptor, coined SURF (Speeded Up Robust Features). It approximates or even outperforms previously ... schemes with respect to repeatability, distinctiveness, and robustness, yet can be computed and compared much...
- Referenced in 250 articles
- remarkably improved from previous schemes in robustness and accuracy. The convergence rate is shown...
Robust Control Toolbox
- Referenced in 138 articles
- Robust Control Toolbox™ provides functions, algorithms, and blocks for analyzing and tuning control systems ... performance and robustness. You can create uncertain models by combining nominal dynamics with uncertain elements ... techniques let you design controllers that maximize robust stability and performance. The toolbox automatically tunes...
- Referenced in 238 articles
- quality. We discuss ways to improve the robustness and the performance, but our aim here...
- Referenced in 225 articles
- deficient covariance matrix, and we provide a robust and reliable Lanczos algorithm which -- despite...
- Referenced in 158 articles
- BerkMin: A fast and robust SAT-solver. We describe a SAT-solver, BerkMin, that inherits ... Experiments show that our program is more robust than Chaff being able to solve more...
- Referenced in 210 articles
- these platforms. Therefore, their vulnerability and robustness against physical attacks, e.g., state...
- Referenced in 203 articles
- implemented with the goal of providing robust time integrators and nonlinear solvers that can easily...
- Referenced in 172 articles
- oriented design techniques. At the same time, robustness issues were considered and enhancement made...
- Referenced in 166 articles
- MINLP). KNITRO is highly regarded for its robustness and efficiency. KNITRO provides a wide range...
- Referenced in 91 articles
- clustering and K-means clustering are not robust to missing data, and may lose effectiveness ... different real data sets, and assessed the robustness of the imputation methods to the amount ... that KNNimpute appears to provide a more robust and sensitive method for missing value estimation...
- Referenced in 97 articles
- robust gradient sampling algorithm for nonsmooth, nonconvex optimization The authors describe a practical and robust...
- Referenced in 71 articles
- Robust optimization made easy with ROME We introduce ROME, an algebraic modeling toolbox ... class of robust optimization problems. ROME serves as an intermediate layer between the modeler ... optimization solver engines, allowing modelers to express robust optimization problems in a mathematically meaningful ... used to model (1) a service-constrained robust inventory management problem, (2) a project-crashing...