
RBoost
 Referenced in 3 articles
[sw29975]
 robust to the noisy data compared with AdaBoost. RBoost1 and RBoost2 optimize a nonconvex loss ... robustness of the proposed algorithms to the noisy training and testing samples. Experimental results...

ACOSampling
 Referenced in 5 articles
[sw41786]
 based on the idea of ant colony optimization (ACO) to address this problem. The algorithm ... starts with feature selection technology to eliminate noisy genes in data. Then we randomly ... informative majority samples and search the corresponding optimal training sample subset. At last, the statistical...

convex_learning
 Referenced in 4 articles
[sw32735]
 convexity, globally optimal solutions are further computed numerically for applications with incomplete, noisy and blurry...

BayesianOptimization.jl
 Referenced in 1 article
[sw42275]
 Bayesian optimization is a global optimization strategy for (potentially noisy) functions with unknown derivatives. With ... alternatives, making it well suited for the optimization of costly objective functions. Well known examples...

PSOFuzzySVMTMH
 Referenced in 3 articles
[sw27664]
 protein sequences. The noisy and extraneous attributes are eradicated using an optimization selection technique, particle...

NARROMI
 Referenced in 6 articles
[sw24066]
 optimization (RO) and information theorybased mutual information (MI). In the proposed algorithm, the noisy...

TVRDART
 Referenced in 23 articles
[sw27583]
 solves the discrete reconstruction problem within an optimization framework inspired by compressive sensing to steer ... more accurate reconstruction than existing algorithms under noisy conditions from a small number of projection...

FEYNMAN
 Referenced in 5 articles
[sw06056]
 noisy environments. The investigation of these and related questions often requires a search or optimization...

Cirq
 Referenced in 7 articles
[sw34753]
 software library for writing, manipulating, and optimizing quantum circuits and then running them against quantum ... abstracting them away, because, in the Noisy IntermediateScale Quantum (NISQ) regime, these details determine...

EKF/UKF Toolbox
 Referenced in 4 articles
[sw21920]
 optimal filtering toolbox for Matlab. Optimal filtering is a frequently used term for a process ... dynamic system is estimated through noisy and indirect measurements. This toolbox mainly consists of Kalman ... toolbox is not to provide highly optimized software package, but instead to provide a simple...

ZOOpt
 Referenced in 2 articles
[sw22396]
 particularly focuses on optimization problems in machine learning, addressing highdimensional, noisy, and largescale...

MOUGH
 Referenced in 2 articles
[sw36675]
 transform is proposed, voting using GMMs and optimized via expectationmaximization that is capable ... based on a training dataset of (possibly noisy) images with only crude estimates of scale ... each image. Further modifications are proposed to optimize the algorithm for tracking. The method...

Deep Speech
 Referenced in 6 articles
[sw40429]
 tend to perform poorly when used in noisy environments. In contrast, our system does ... approach is a welloptimized RNN training system that uses multiple GPUs, as well ... test set. Deep Speech also handles challenging noisy environments better than widely used, state...

FacetNet
 Referenced in 16 articles
[sw20426]
 this approach is inappropriate in applications with noisy data. In this paper, we propose FacetNet ... which is guaranteed to converge to an optimal solution. We perform extensive experimental studies...

IDRLnet
 Referenced in 1 article
[sw39547]
 metrics, and optimizers within Python. Furthermore, it provides functionality to solve noisy inverse problems, variational...

krisp
 Referenced in 1 article
[sw14717]
 also known as Gaussian process regression) and optimization of deterministic simulators. The toolbox consists ... creation of kriging model for deterministic or noisy data (correlation kernels, hyperparameter estimation, prediction ... validation). 2. methods implementing Expected Improvement based optimization for time consuming deterministic functions...

FPDclustering
 Referenced in 3 articles
[sw15462]
 used with nonspherical clusters, outliers, or noisy data. Facto PDclustering (FPDC ... linear transformation of variables and a cluster optimizing the PDclustering criterion. It works...

PyBOBYQA
 Referenced in 1 article
[sw32721]
 BOBYQA: DerivativeFree Optimizer for BoundConstrained Minimization. PyBOBYQA is a flexible package ... objective function are expensive and/or noisy...

SINDyPI
 Referenced in 4 articles
[sw40367]
 nonlinearities. The SINDyPI framework includes multiple optimization algorithms and a principled approach to model ... equations and conservation laws from limited and noisy data. In particular, we show that...

trajectory
 Referenced in 1 article
[sw22650]
 circular motion under the conditions of incomplete noisy measurements is formulated and implemented ... shown how to apply algorithms for discrete optimal filtering to the evaluation of such...